Master FinOps principles and tools on Google Cloud Platform. Learn to monitor, control, and optimize cloud costs through hands-on strategies, real-world use cases, and GCP-native solutions and frameworks.

Key Features

• Learn FinOps tailored for GCP, from cost allocation and budgeting to cost governance and value realization.
• Optimize GCP spend, align engineering with finance, and support business efficiency.
• Through real-world use cases, hands-on tutorials, and tool-driven workflows using GCP-native services.

Book Description

What you will learn

• Apply FinOps principles to the Google Cloud environment, including AI workloads
• Establish the FinOps operating model, define roles, and enable cross-functional collaboration
• Navigate GCP billing models, pricing structures, FOCUS specs, and cost allocation strategies
• Set budgets, quotas, and alerts to manage cloud spend proactively
• Analyze usage with BigQuery and visualize spend trends in Looker Studio
• Optimize compute, storage, networking, and databases using FinOps Hub and native GCP tools
• Enforce financial guardrails to support a strong FinOps culture across the organization

Who this book is for

This book is ideal for FinOps practitioners, cloud architects, platform engineers, and DevOps professionals who want to optimize cloud spend and implement financial accountability in Google Cloud environments. A working knowledge of GCP services, billing concepts, and basic cloud operations is assumed. Familiarity with tools like BigQuery and GCP IAM will be helpful but not mandatory.

L’odorat est sans doute le sens le plus méconnu de tous. Pourtant, il joue un rôle essentiel dans la vie des êtres humains comme dans celle de l’ensemble des êtres vivants. Depuis des millions d’années, les odeurs sont utilisées par les plantes et les animaux pour alerter, attirer, se reconnaître, s’orienter ou tromper leurs ennemis. Des plants de tabac qui diffusent un signal d’alarme olfactif aux moustiques irrésistiblement attirés par les pieds en sueur, des lys qui imitent l’odeur d’un animal en décomposition aux manchots qui reconnaissent leur partenaire entre mille grâce à ses effluves, Bill S. Hansson propose un fascinant voyage au cœur de l’odorat. Requin, saumon, chien, souris, papillon, crabe ou albatros... tous ont un « nez » remarquable !

L’auteur dévoile les étonnants mécanismes de la communication chimique et montre combien le monde des odeurs a évolué au fil du temps. Les senteurs perçues par nos ancêtres étaient bien différentes des nôtres, et les technologies de demain transformeront à leur tour notre univers olfactif.

À la fois passionnant, accessible et foisonnant d’anecdotes, ce livre ouvre les portes d’un monde invisible qui façonne pourtant la vie.

Lire la préface d'Emmanuelle Joly, directrice de recherche INRAE, spécialisée dans la communication chimique chez les insectes

Build production-ready digital creatures using practical ZBrush recipes and Maya workflows covering sculpting, retopology, UDIMs, detailing, and production export for VFX and animation pipelines Free with your book: DRM-free PDF version + access to Packt's next-gen Reader*

Key Features

• Create production-ready creatures using practical ZBrush sculpting recipes
• Build efficient workflows for blocking anatomy, detailing, and preparing assets for VFX and animation
• Optimize high-resolution creature sculpts using retopology, Layers, and UDIMs
• *Email sign-up and proof of purchase required

Book Description

What you will learn

• Apply professional creature sculpting workflows in ZBrush
• Use DynaMesh, ZSpheres, and Sculptris Pro effectively
• Sculpt clear primary, secondary, and tertiary forms
• Organize and optimize UVs using UDIM workflows
• Create custom brushes, Insert Multi Mesh brushes, and alphas for complex surface details
• Divide complex models to maximize sculpting resolution
• Export clean meshes and generate multi-resolution maps
• Optimize high-resolution sculpts using Decimation Master

Who this book is for

Ideal for digital sculptors, creature artists, and 3D modelers with a basic understanding of ZBrush who want to develop production-ready workflows. You'll benefit most if you're familiar with the ZBrush interface, navigation, brushes, and core sculpting tools. Basic knowledge of Maya's interface and modeling workflows is recommended. Whether you're a student with prior ZBrush experience, a freelancer improving your workflow, or a junior to intermediate artist preparing for a career in the industry, this book provides practical recipes, production insights, and industry-grade techniques.

Learn how to add monetization to a Roblox game with game passes, developer products, purchase flows, analytics, and quality checks using practical workflows designed for experienced Roblox developers

Key Features

• Choose the right monetization model using game passes and developer products
• Build and validate a complete purchase flow from interaction to confirmation
• Instrument analytics and use player signals to guide iterative improvements

Book Description

What you will learn

• Choose between game passes and developer products
• Prepare Roblox Studio for a monetized workflow
• Build a complete client-server purchase flow
• Trigger purchases through in-world interactions
• Instrument analytics to capture meaningful player signals
• Run smoke tests and identify common monetization issues
• Diagnose player behavior using analytics and quality checks
• Extend monetization safely without unnecessary complexity

Who this book is for

This nanobook is for Roblox developers who already know how to navigate Roblox Studio, understand Luau fundamentals, and have a working gameplay loop in place. It focuses on turning an existing game into a monetized experience by implementing respectful purchase flows, basic analytics, and operational best practices. Prior knowledge of Roblox Studio, scripting, and publishing experiences is assumed.

This book provides a systematic study of facial expression recognition technology for human-computer interaction, covering the complete processing pipeline from image preprocessing to expression classification. The research presented in this book, supported by the National Natural Science Foundation of China, offers a comprehensive framework for facial expression recognition, including a fractional-step color constancy algorithm for complex illumination conditions, multi-feature fusion strategies, and theoretical innovations with practical engineering applications.

This book will be a valuable reference for graduate students and advanced undergraduates studying computer vision and related subjects, as well as for researchers and engineers working in artificial intelligence, computer vision, affective computing, and human-computer interaction.

Transform cyber threat intelligence operations with multi-agent AI workflows. Automate intelligence collection, corroborate threat signals, apply structured analysis, and produce tailored, high-fidelity intelligence at scale.

Key Features

• Build multi-agent AI pipelines to automate the cyber threat intelligence lifecycle
• Automate threat intelligence workflows for collection and cross-source corroboration
• Apply Structured Analytic Techniques to automated threat intelligence workflows

Book Description

What you will learn

• Build multi-agent AI pipelines for CTI workflows
• Automate intelligence requirements and collection planning
• Corroborate cross-source threat signals to score breach fidelity
• Scaffold Structured Analytic Techniques with AI agents
• Generate argument maps and tailored intelligence reports
• Automate secure primary research, forecasting, and threat hunting

Who this book is for

This book is for cyber threat intelligence analysts looking to scale their daily workflows with agentic AI and automation. Security engineers, detection engineers, and SOC practitioners seeking to automate intelligence operations will also benefit. To get the most out of the hands-on projects, you should have an intermediate understanding of cybersecurity, experience with threat intelligence methodologies, and basic Python 3.x scripting skills. No prior expertise in AI expert is required.

Build modern data and AI platforms in the Snowflake AI Data Cloud with practical recipes for data governance, automation, Cortex AI, observability, and intelligent application development.

Key Features

• Apply 100+ practical recipes for data engineering, data governance, and AI development
• Build secure, scalable data solutions using Snowflake platform capabilities
• Learn when and why to apply each pattern for real-world success
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

What you will learn

• Build secure Snowflake environments using roles and policies
• Create automated data pipelines with stages, tasks, and streams
• Ingest and transform data using Openflow and Snowflake
• Implement data governance with tags, masking policies, and classification
• Work with structured, semi-structured, and unstructured data
• Build AI-ready solutions using Snowflake Cortex
• Improve resilience with cloning and Time Travel
• Learn when and why to apply each pattern effectively

Who this book is for

This book is for data professionals designing, building, and operating modern data and AI platforms on the Snowflake AI Data Cloud. Data engineers, data architects, analytics engineers, AI engineers, developers, and technical leaders will gain practical implementation skills and architectural insight. Basic SQL and data warehousing knowledge is recommended. Whether you’re building governed data platforms, AI-ready architectures, intelligent applications, or enterprise analytics solutions, this book provides proven patterns and practical, real-world guidance.

Master system design and behavioral interviews with practical frameworks, real-world design case studies, leadership storytelling techniques, and AI-assisted strategies for senior software engineering roles.

Key Features

• Design scalable systems using modern architectures and real-world case studies
• Use a structured framework for system design interviews, including Agentic AI
• Develop Behavioral Intelligence to read the signals behind questions
• Master STAR-R and leadership storytelling for senior roles
• Get a free PDF eBook with print or Kindle purchase

Book Description

What you will learn

• Apply a structured, repeatable approach to system design
• Design scalable distributed systems with confidence
• Evaluate architectural trade-offs for real systems
• Apply core design patterns and algorithms
• Design AI-native and agentic systems
• Build high-signal stories with STAR+R and a story bank
• Craft senior-level leadership and impact stories
• Learn how Big Tech evaluates you, including the scorecard
• Speak the language of DORA, RACI, and risk heatmaps
• Use AI to prepare, practice, and sharpen your stories

Who this book is for

Software engineers, backend developers, senior developers, solution architects, engineering managers, executives and computer science students preparing for technical interviews will benefit from this book. It is also valuable for professionals targeting senior engineering roles at product companies and FAANG organizations. Readers should have a basic understanding of software development, data structures, algorithms, and object-oriented programming.

Nous devons au vivant nos aliments, notre eau, nos matériaux et notre bonne santé. Pourtant, par nécessité puis par confort, nous avons appris à le contenir, à le museler… jusqu’à menacer les fonctions qu’il assure et dont nous dépendons. Transformer durablement nos comportements suppose d’abord de changer notre regard.
Dans cet ouvrage, l’auteur nous accompagne sur les chemins de nos campagnes, de nos villes et de nos montagnes, à la rencontre de scientifiques et de protecteurs de la nature. Il nous apprend à reconnaître, dans notre santé comme dans nos paysages, le rôle invisible mais vital de la biodiversité. Progressivement se dessine une autre manière de se relier à la nature, nourrie tant par l’expérience sensible que par la compréhension de notre dépendance envers elle.
Nous ne sommes pas en guerre avec le vivant. Et notre avenir dépend de la paix que nous saurons tisser avec lui. 

Build reliable agent-orchestrated engineering simulation workflows with AG2/AutoGen, validation gates, auditable artifacts, failure recovery, and a practical heat-diffusion example.

Key Features

• Build planner-reviewer-controller-executor workflows with AG2/AutoGen
• Apply validation gates, audit trails, and fail-fast recovery to simulations
• Follow a runnable heat-diffusion example from request to traceable report

Book Description

What you will learn

• Map engineering simulations into explicit orchestration stages
• Define planner, reviewer, controller, and executor roles
• Implement an AG2/AutoGen workflow around a trusted simulation
• Validate requests, plans, tool calls, and simulation outputs
• Diagnose failures and apply repair, re-planning, or escalation
• Extend the pattern to CFD, FEA, parameter sweeps, cloud, and HPC

Who this book is for

This book is for ML/AI engineers, simulation engineers, and technical workflow owners who want to coordinate multi-step engineering simulations with agentic AI. Familiarity with Python and basic simulation workflows will help you follow the runnable examples. No prior AG2/AutoGen experience is required.

Progress from your first conversation to completing professional assignments, creating advanced AI workflows, and and enhancing your career.

Key Features

• Follow a structured visual learning path from simple chatbot to reliable professional AI partner.
• Learn through practical activities and complete projects instead of abstract explanations.
• Develop safe, responsible practices for reviewing AI output and protecting information.

Book Description

What you will learn

• Set up ChatGPT and become familiar with the interface
• Write clear prompts and refine responses through conversations
• Use web search, deep research, documents, images, and data
• Create professional documents, presentations, and visual reports
• Build tested, shareable skills and specialized custom GPTs
• Connect plugins, apps, and trusted MCP servers
• Design end-to-end workflows for complex assignments
• Use AI to advance your career and income

Who this book is for

This book is for professionals, entrepreneurs, freelancers, consultants, marketers, salespeople, writers, recruiters, analysts, managers, students, and career changers. It is suitable for complete beginners as well as existing ChatGPT users who want a more structured learning experience. No coding knowledge or previous AI experience is required.

RAMSES, l'ouvrage prospectif de référence, propose chaque année à un large public (étudiant, enseignant, manager, journaliste, diplomate...) les clés et repères indispensables pour décrypter les évolutions du monde, selon un credo simple : "Éclairer, ne rien imposer".

RAMSES 2027  interroge le monde d’après autour de 3 thématiques.

Assorti d'un riche appareil documentaire (annexes statistiques, chronologie, cartographie originale) et de vidéos des auteurs venant compléter et approfondir  les analyses de l'ouvrage.

Bridge business goals and technical execution to build, deploy, and govern generative AI solutions on AWS

Key Features

• Align business strategy with practical generative AI use cases on AWS
• Build MVPs, agents, and production systems with Bedrock and SageMaker
• Apply governance, scaling, and responsible AI practices across industries
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

What you will learn

• Understand how generative AI creates business value
• Compare models, prompts, fine-tuning, and RAG
• Navigate the AWS generative AI stack with confidence
• Prepare data and select models for real use cases
• Build MVPs and production-ready AI applications
• Apply governance, ethics, and responsible AI controls
• Evaluate agentic AI patterns and emerging trends
• Measure impact across enterprise AI initiatives

Who this book is for

Developers, solutions architects, technical product managers, innovation leaders, CTOs, and business decision-makers who want to plan, build, and scale generative AI solutions on AWS. It is ideal for teams moving from experimentation to production and for leaders aligning AI initiatives with business outcomes. A basic understanding of cloud concepts and software delivery is helpful.

Ce manuel de référence, tout en couleur et richement illustré, offre un panorama
complet des Sciences de la Terre et de l’Univers, du Big Bang à l’origine de l’Homme en passant par toutes les spécialités qui en font la richesse : tectonique des plaques, minéralogie, géochimie, géomorphologie, sédimentologie, etc. Entièrement mise à jour, cette 18e édition est parfaitement adaptée au programme des étudiants en Sciences de la vie et de la Terre ou en Géographie, ainsi qu’aux candidats aux concours de l’enseignement.

Learn Unreal Engine 5 through a hands-on game project, progressing step by step from editor basics and Blueprints to AI, UI, cinematics, polish, and packaging Free with your book: DRM-free PDF version + access to Packt's next-gen Reader*

Key Features

• Build a complete third-person game through a practical, step-by-step workflow
• Develop gameplay systems using Blueprints without writing code
• Create levels, a player character, enemy AI, UI, gameplay, and an opening cutscene in one project
• Solve common problems encountered during game development
• *Email sign-up and proof of purchase required

Book Description

What you will learn

• Build and prototype 3D game levels using Unreal's Level Editor
• Create gameplay logic visually with Blueprints (no coding required)
• Import, animate, and set up a playable character
• Configure player controls using Unreal's Enhanced Input system
• Build enemy AI that can sense and chase the player using Behavior Trees
• Design menus and HUDs with Unreal Motion Graphics (UMG)
• Produce an introductory cut-scene using the Sequencer
• Polish your game and package it into a standalone playable file

Who this book is for

This book is for aspiring game developers, students, and hobbyists who want to learn Unreal Engine 5 through hands-on game development. Whether transitioning from another engine or starting fresh, readers will find step-by-step guidance accessible. No prior Unreal Engine or programming experience is required. You should have basic computer skills and be familiar with common video game controls, mechanics, and objectives. It also suits artists, designers, and programmers who want to learn Unreal Engine 5 through practical, hands-on game development and prototyping.

Turn vibe coding into reliable software delivery by using specs, guardrails, tests, and workflows that keep AI-generated systems coherent

Key Features

• Turn fast AI coding into scalable software architecture
• Use specs, tests, and guardrails to control generated code
• Apply workflows for agents, reviews, CI/CD, and team adoption

Book Description

What you will learn

• Use specs to guide AI-assisted software delivery
• Manage context to reduce prompt entropy and drift
• Design guardrails for generated code and agents
• Build tests that check architectural intent
• Apply review workflows for AI-generated changes
• Handle prompt injection and untrusted context safely
• Use CI/CD and orchestration for multi-agent work
• Track prompts, model choices, and intent in Git

Who this book is for

This book is for developers, product managers, engineers, architects, and technical leads who are already using or evaluating AI-assisted coding and need stronger control over architecture, quality, security, and team workflow. Familiarity with software delivery, code review, testing, and modern development tools will help readers get the most from the book.

Master modern mobile forensics with practical techniques for iOS and Android, covering data acquisition, artifact analysis, and data recovery in real-world investigations.

Key Features

• Acquire and analyze artifacts across devices, cloud ecosystems, and backups
• Apply advanced forensic techniques to recover deleted data from mobile devices
• Understand the limitations of modern mobile forensics and approaches to navigate them

Book Description

What you will learn

• Understand mobile security architectures, including encryption, sandboxing, and data protection mechanisms
• Perform advanced data acquisition and extraction from modern iOS and Android devices
• Identify and interpret key forensic artifacts such as messages, call logs, app data, and system databases
• Work with SQLite databases, WAL files, and encoded application data formats
• Use both open-source and commercial forensic tools in real-world investigation workflows
• Understand the limitations of modern mobile forensics and practical approaches to overcome them

Who this book is for

This book is designed for digital forensic practitioners and investigators looking to build foundational skills in mobile forensics across modern iOS and Android platforms. It is also valuable for security professionals, incident responders, and researchers interested in understanding mobile device internals, application data, and forensic artifact analysis. A foundational understanding of digital forensics and basic familiarity with operating systems will help readers get the most from this book, though prior forensic experience is not mandatory.

Build fast and scalable web apps with React 19 and Next.js 16 by applying proven design patterns, avoiding common anti patterns, and shipping production features with testing, CI/CD, and practical AI assisted workflows

Key Features

• Updated for React 19 & Next.js 16 with modern, production-ready design patterns
• Full-stack React mastery with Express, PostgreSQL, Drizzle ORM & CI/CD workflows
• Build scalable, SEO-first apps and boost developer productivity with AI tools like ChatGPT and Claude
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

What you will learn

• Manage state with Redux Toolkit, Zustand, and new React hooks
• Implement authentication, authorization, and role-based access control with NextAuth.js
• Write comprehensive tests using Jest, React Testing Library, and Playwright for E2E scenarios
• Deploy to production with caching, monitoring, and optimization strategies
• Apply structured prompt templates for refactors, bug triage, and ADR first-drafts
• Use Claude/ChatGPT to draft components, convert JS-TS, and generate tests with coverage goals

Who this book is for

This book is for intermediate to advanced React developers eager to master React and Next.js. Whether you're a frontend developer, full-stack engineer, or tech lead looking to upgrade your skills, this book provides advanced patterns and production-ready techniques you need. It's ideal for developers transitioning from traditional client-side React to server-centric architectures and those seeking to build performant, scalable applications. Teams interested in safe AI-assisted workflows and tools will gain practical, real-world guidance to accelerate delivery without sacrificing quality.

Cet ouvrage permet d’appliquer les bases de la mécanique des fluides aux  problématiques industrielles actuelles. Partant des définitions et propriétés des  fluides et allant jusqu’à la notion d’écoulements compressibles, il aborde la  statique, la cinématique, les pertes de charge, les équations de Navier-Stokes,  la similitude, la rhéologie, ainsi que les écoulements turbulents. Dans cette  nouvelle édition, de nombreuses améliorations ont été apportées tant sur les  parties de cours que sur les exercices d’application.

Build a strong PowerShell foundation by learning command discovery, modules, variables, objects, pipelines, operators, conditional statements, and loops, with clear examples that prepare you to start scripting and automating everyday tasks

Key Features

• Build a solid PowerShell foundation through commands, modules, variables, objects, and operators
• Learn to work effectively with the PowerShell pipeline and object-based output
• Write practical logic using comparisons, conditions, switch statements, and loops

Book Description

What you will learn

• Navigate PowerShell and use its help and command-discovery features
• Find, install, and use PowerShell modules
• Create and manage variables, arrays, and hashtables
• Work with objects, pipelines, filtering, sorting, and formatting
• Use arithmetic, comparison, logical, assignment, and other operators
• Build decision-making logic with if, elseif, else, and switch
• Automate repetitive logic using PowerShell loops
• Use break and continue to control script execution

Who this book is for

This book is for aspiring system administrators, IT professionals, developers, students, and complete beginners who want to learn PowerShell from the ground up. It introduces the PowerShell command line and help system before progressing through modules, variables, arrays, hashtables, objects, operators, conditional statements, and loops. Basic familiarity with operating systems is helpful, but no prior PowerShell experience is required.

Face au réchauffement climatique, la surchauffe des bâtiments tertiaires est un  enjeu central de confort, de santé publique et de performance énergétique. Qu'ils soient à construire ou existants, il est indispensable de penser et adapter les bâtiments à la chaleur pour garantir des lieux de travail, d’apprentissage ou de soins réellement résilients. Dans une approche complète, rigoureuse et accessible pour les acteurs du bâtiment public et privé, cet ouvrage explore :

• Les causes et les impacts systémiques du réchauffement sur les bâtiments, les usages et les territoires urbains.
• L’analyse technique du confort d’été, de la physiologie humaine aux indicateurs de surchauffe.
• Les stratégies de conception et de rénovation, des solutions passives aux systèmes techniques actifs.
• L’adaptation des usages et l’exploitation intelligente des bâtiments pour répondre aux épisodes extrêmes.

Learn the complete MetaHuman production pipeline in Unreal Engine 5.7, from character creation and animation to motion capture, facial performance, cinematic rendering, Mesh to MetaHuman, Blender, and production-ready workflows Free with your book: DRM-free PDF version + access to Packt's next-gen Reader*

Key Features

• Learn the complete MetaHuman production pipeline using Unreal Engine 5.7
• Create production-ready digital humans with body animation, facial motion capture, and cinematic rendering
• Extend your workflow with Mesh to MetaHuman, Blender, Maya, Houdini, and professional production tools

Book Description

What you will learn

• Create, customize, and assemble production-ready MetaHumans in Unreal Engine 5.7
• Animate MetaHumans using Mixamo, DeepMotion, MetaHuman Animator, and Control Rig
• Capture realistic facial performances using an iPhone or a standard webcam
• Create custom clothing that can be repurposed across all MetaHumans with physics-based cloth simulations
• Create cinematic sequences using Level Sequencer, lighting, cameras, and Movie Render Queue
• Build custom MetaHumans with Mesh to MetaHuman and create hair grooms using Blender
• Integrate professional tools including Blender, Maya, Houdini, Marvelous Designer, Character Creator, and other production plugins

Who this book is for

This book is for filmmakers, game developers, technical artists, animators, students, and digital content creators who want to master the complete MetaHuman production pipeline using Unreal Engine. Whether you're producing game cinematics, animated films, virtual productions, or interactive experiences, you'll learn practical workflows that take you from creating a digital character to producing a final cinematic performance. A basic understanding of Unreal Engine is recommended.

Soils play a vital role in ecosystems, food security and health. To support public policies aimed at preserving soil functions and conservation, a multidisciplinary group of 19 experts from various public research organisations, coordinated by INRAE, analysed the scientific literature on soil quality and health. They have compiled the main available resources and key considerations for conducting assessments based on the ecological functions performed by soils. Around fifty physical, chemical and biological indicators are linked to an interpretation framework that specifies measurement or calculation methods, as well as reference values for interpretation.

The selection of indicators depends on the assessment’s objectives, such as drafting urban planning documents or zoning agricultural plots for land consolidation. To adequately choose these indicators, select the interpretation framework and determine the monitoring grid (spatial and temporal), and whether to aggregate certain indicators, the assessment’s goals must be carefully considered.

This approach fosters dialogue among stakeholders from diverse social and political backgrounds, enabling them to collectively reflect on the nature of soils and the future of land use. 

This book is intended for non-experts with a solid understanding of the subject, including decision-makers, professionals, and representatives of non-profit organisations and public services responsible for environmental and urban planning policies. More broadly, it is aimed at anyone interested in the public debate on soil quality and health.

Description
Kubernetes has become the backbone of modern cloud-native applications, but it is also a high-value target for attackers. As organizations rapidly adopt containers, service meshes, and automation, securing Kubernetes clusters has become an active security battle.

This book takes a hands-on, end-to-end approach to Kubernetes security. It begins by exploring real-world attack surfaces, guiding readers through container enumeration, RBAC abuse, and cluster takeover techniques. The focus then shifts to defense, covering Kubernetes audit log analysis, runtime detection, monitoring with Prometheus, and incident response. From an offensive perspective, you will learn to scan exposed services, deliver reverse shell payloads, and enumerate internal cluster metadata. Switching to defensive operations, you will conduct threat hunting using API audit logs, correlate runtime telemetry to reconstruct incident kill chains, and run automated tools. Each chapter is built around practical demonstrations that mirror how attacks and detections occur in real environments.

By the end of this book, readers will gain real-world proficiency in both offensive cluster exploitation and defensive forensic analysis in Kubernetes environments. They will be able to identify and exploit common weaknesses, detect malicious behavior, and design Kubernetes clusters.

What you will learn
? Exploit real Kubernetes misconfigurations used in production attacks.
? Perform container enumeration, breakout, and cluster escalation techniques.
? Detect attacks using audit logs and runtime security tools.
? Hunt threats with Falco, Sysdig, Prometheus, and SIEM.
? Analyze network traffic for lateral movement and data exfiltration.
? Reconstruct Kubernetes attack kill chains and respond effectively.

Who this book is for
This book is for security engineers, DevSecOps practitioners, Kubernetes administrators, red teamers, and SOC analysts securing cloud-native environments. Readers should possess basic Linux administration skills, familiarity with Docker container fundamentals, and a foundational understanding of networking concepts and kubectl command-line usage.

Table of Contents
1. Introduction to KubePwn Labs
2. Learning Kubernetes Architecture
3. KubePwn Lab Setup
4. Infiltrating Kubernetes Cluster
5. Enumerating Kubernetes like a Pro
6. Privilege Escalation to Cluster Takeover
7. Threat Hunting and Forensics
8. Identifying Misconfigurations in K8s Cluster

Description
Modern applications demand architectures that can scale, evolve, and adapt to changing business requirements. Designing successful microservices requires more than breaking an application into smaller services; it requires understanding deployment and operational practices. This book presents a practical, domain-driven approach to understanding how modern microservices architecture is designed and operated.

The book begins by establishing the fundamentals of microservices, comparing monolith and microservices architectures while introducing loose coupling, strong cohesion, and data decomposition. It then demonstrates how business growth drives the transition to Event Storming and architectural patterns to define service boundaries before applying these principles across the Product Catalog, search, customer, cart, and checkout domains through data architectures, services, and deployment infrastructure with Micro Frontends, API Gateway, CQRS, EDA, service discovery, service mesh, circuit breaker, containerization, and container orchestration, further exploring the integration of AI, ML, and data pipelines support, recommendations, fraud detection, and pricing intelligence.

By the end of this book, the readers will be equipped with the expertise to move beyond theoretical concepts, providing the practical toolkit and design patterns necessary to architect, scale, and manage sophisticated microservices ecosystems in any enterprise environment.

What you will learn
? Understand core microservices architecture concepts.
? Design services using Domain-Driven Design principles.
? Transforming and modernizing monolithic applications into microservices.
? Embracing infrastructure, DevOps, and security.
? Adopting microservices across the organization.
? Unlocking true AI value with existing microservices.

Who this book is for
This book is intended for aspiring engineers, students, software developers, QA engineers, solution architects, and enterprise architects with programming fundamentals who want a practical roadmap to designing microservices, mastering distributed systems, and establishing a scalable foundation for AI integration.

Table of Contents
1. Introduction to Microservices
2. Splitting Monolith
3. Domains, Contexts and Patterns
4. Weaving Product Catalog
5. Weaving Domain Search
6. Weaving Customer Domain
7. Weaving Cart Domain
8. Weaving Order Domain
9. Scaling the Weave from Pattern to Production
10. Weaving AI into Microservices

Description
This book argues that AI is not simply software running on infrastructure; it is reshaping the infrastructure itself. As compute scales from megawatts to gigawatts, data centers evolve into AI factories, where energy, data, and silicon are fused into systems that continuously produce intelligence.

The book presents AI factories as the industrial backbone of the intelligence age, built on the foundational pillars of compute, network, power, sustainability, security, and governance. It moves from the foundations of AI factories, exascale computing, compute sovereignty, and efficient compute systems into multi-layered architectures, secure training systems, AI networking, power systems, autonomous grid systems, advanced cooling technologies, circular data centres, net-zero operations, modular construction, and water-neutral operations. Each chapter builds toward understanding how AI infrastructure is designed, operated, and governed as a living system.

By the end of this book, readers will gain a deeper understanding of the technical, operational, and strategic principles required to design and manage AI data centres. The book prepares leaders, architects, and innovators to navigate the future of intelligent infrastructure, where AI factories become essential systems for building, operating, and governing intelligence at scale, and where intelligence is manufactured, energy is cognition, and infrastructure itself begins to think.

MESURER la Terre a été, depuis l’Antiquité, l’un des nombreux défis des scientifiques. C’est l’histoire de cette mesure que raconte ce livre, dont le titre est emprunté à celui de l’ouvrage publié au XVIIe siècle par l’un des plus glorieux géodésiens, Jean Picard. 
Déjà, pendant l’Antiquité, les savants avaient cherché à connaître les dimensions de notre globe dont ils savaient parfaitement qu’il n’était pas plat, mais sphérique, et avaient obtenu des résultats tout à fait corrects. Mais il a fallu attendre le XVIe siècle pour qu’apparaissent les méthodes modernes de mesure de la Terre, et ainsi les premières cartes géographiques exactes, loin des élucubrations fantaisistes médiévales. La principale difficulté que les géographes aient rencontrée est la détermination des longitudes, et les deux siècles qui suivent ont connu leurs tâtonnements et essais plus ou moins fructueux pour résoudre le problème. Quant aux marins, ils ont dû attendre la fin du XVIIIe siècle pour que le perfectionnement des chronomètres leur permette enfin de savoir où ils étaient vraiment. 
Le XIXe siècle a connu une véritable explosion de la géodésie, avec d’immenses travaux partout dans le monde, tandis que la cartographie devenait bien plus précise et que le développement des empires coloniaux précisait la connaissance de territoires inexplorés. 
On pourrait considérer qu’aujourd’hui, tout cela est devenu un peu caduc avec le développement du GPS, mais parions que cette longue et palpitante histoire suscitera tout de même la curiosité et l’enthousiasme des lecteurs !

Description
Domain-Driven Design (DDD) is a software development philosophy centered on aligning complex codebases with the core business domain. By establishing a Ubiquitous Language shared between developers and domain experts, it bridges the gap between technical implementation and business strategy.

This book serves as a practical, accessible guide to mastering the art of translating business needs into clean, adaptable code. It explores the historical context and foundational principles of DDD, emphasizing the collaborative communication required to build a shared understanding of the domain. The text delves deeply into both Strategic and Tactical Design, using real-world case studies and concrete examples to illustrate how to model complex business processes. Additionally, it addresses practical challenges, such as managing organizational complexities, handling legacy systems, and integrating DDD with Agile or Lean methodologies.

By the end of this book, you will understand how to define domains, map system relationships, and utilize Tactical Design patterns to implement robust business rules in code. You will know how to iteratively refine software models through refactoring to ensure they remain aligned with evolving business goals. Ultimately, you will be equipped with the mindset and practical skills needed to overcome real-world architectural complexities, leverage modern software methodologies, and cultivate the collaborative art of building highly valuable software solutions.

Cette collection entraîne les étudiants aux devoirs sur table, mais leur permet aussi de parfaire leur méthode de décryptage d’un énoncé dans le but d’obtenir la note maximum, et ce tout au long de l’année de prépa ainsi qu’aux concours.

• 30 devoirs (livres de 1re année).
• 20 devoirs (2e année) et des sujets d’annales corrigées.
• Une introduction générale de méthodologie sur comment réussir son année de prépa.
• Des renvois vers des notions de cours.
• Les mots essentiels et les formules à comprendre et à connaître.
• Un index thématique pour cibler les notions de son choix.

Description
Test-driven development (TDD) is a development approach that flips traditional coding on its head by writing tests before writing the actual code. This powerful methodology helps developers write cleaner, more maintainable, and bug-resistant software. In the world of Python, TDD is not just a best practice; it is a game-changer. This book is your hands-on guide to mastering TDD the Pythonic way.

This book begins with the fundamentals of TDD, such as what it is, why it matters, and how to set up your development environment for test-first coding. Each chapter introduces you to core concepts like unit testing, test automation with unittest and pytest, mocking, refactoring, and continuous integration. You will build real Python applications through a TDD lens, progressing from simple functions to fully tested modules and components. A few chapters will explore TDD for APIs, working with databases, and using test doubles effectively, and each chapter ends with a practical mini-project to reinforce learning.

By the end of this book, you will not only be comfortable with writing tests first but also confident in designing cleaner architecture and delivering production-ready Python code faster. This book will also empower you to build smarter and ship with confidence.

What you will learn
? Learn TDD principles to write reliable Python code faster.
? Use unittest and pytest to automate Python test coverage.
? Understand mocks and stubs to test isolated components.
? Develop APIs and apps using TDD for real-world readiness.
? Apply CI and refactoring techniques for clean, testable code.
? Design class constructor APIs and validate private object methods.
? Implement JWT authentication and deploy characterization tests on seams.
? Write failing tests first to drive incremental functional implementations.

Who this book is for
This book is for Python developers, QA engineers, automation testers, and software engineers transitioning into test-first coding. A basic understanding of Python programming is required; however, intermediate professionals can skip prior TDD experience to master building reliable applications.

Table of Contents
1. Introduction to TDD and Python Setup
2. Unit Testing with Unittest
3. Embracing Pytest for Simpler Tests
4. Writing Test-first Functions
5. Incremental Implementation with TDD
6. TDD with Classes and Objects
7. Mocking, Stubbing, and Isolating Tests
8. Building a Calculator API with TDD
9. Testing Database Interactions
10. Test Coverage and Refactoring
11. Integrating TDD with Continuous Integration
12. TDD in Teams and Real-World Projects
13. Final Project, Full-stack Task Manager Using TDD
14. Securing, Scaling & Testing Legacy Code

Description
Data contracts are becoming important as organizations move to cloud platforms, data products, and decentralized data ownership. They create clear agreements between data producers and consumers, helping teams reduce broken pipelines, unclear ownership, and trust issues in daily data work. Data Contracts in Action shows how data contracts help establish clear agreements between data producers and consumers, improving trust, reducing operational issues, and creating scalable foundations for modern data ecosystems.

This book takes the reader from the basics of data governance and data quality to the practical use of data contracts in modern data platforms. It explains why governance matters, how data debt grows, and how contracts can define schemas, metadata, validation rules, ownership, and expectations. The readers will learn how to design contract-driven architectures, use standards such as JSON Schema, Avro, Protobuf, YAML, and OpenAPI, apply CI/CD and version control, monitor contract violations, and handle schema evolution.

This book takes the reader from the basics of data governance and data quality to the practical use of data contracts in modern data platforms. It explains why governance matters, how data debt grows, and how contracts can define schemas, metadata, validation rules, ownership, and expectations. The readers will learn how to design contract-driven architectures, use standards such as JSON Schema, Avro, Protobuf, YAML, and OpenAPI, apply CI/CD and version control, monitor contract violations, and handle schema evolution.

Description
Artificial intelligence is reshaping how we live, work, learn, and solve complex problems. For students entering a technology-driven world, understanding the fundamentals of AI is an increasingly valuable skill. This comprehensive guide introduces machine learning, data science, computer vision, and natural language processing in a clear and engaging way for Class X students.

Designed to build both conceptual knowledge and practical skills, the book provides a structured journey through the AI landscape. It covers topics ranging from decision trees to neural networks and introduces the key stages of AI project development, including problem scoping, data acquisition, data exploration, modelling, and evaluation. It also develops important career-readiness skills and introduces responsible AI, ethical practices, and green computing.

By the end of this book, readers will understand fundamental AI concepts and gain confidence in using Python and modern AI tools. Students will be equipped to move from passive users of technology to active creators who can explore ideas and develop their own AI projects. Whether you are a student, educator, or technology enthusiast, this book provides an accessible foundation for learning and creating in an AI-enabled world.

Description
Data is everywhere, but data by itself has little value unless we can learn from it. Let us Learn Machine Learning takes you on a step-by-step journey from raw data to intelligent predictions. Beginning with data preparation and exploration, the book explains how to build, evaluate, and improve machine learning models using techniques such as Linear Regression, Logistic Regression, SVM, KNN, Naive Bayes, Decision Trees, Bagging, Boosting, and more. Along the way, you will learn how to engineer features, select the right models, reduce dimensionality, and deal with real-world challenges such as overfitting and imbalanced datasets.

Written in a simple, practical style, this book focuses on developing intuition as much as technical skill, making machine learning accessible to students, developers, and professionals alike.

Each chapter contains:
? Lucid explanation of the concept.
? Well thought-out, fully working programming examples.
? End-of-chapter exercises to practice the skills learned in the chapter.

What you will learn
? Build a complete, end-to-end ML pipeline - ingest data from CSV, SQL, APIs, and web scraping; clean and preprocess it; and explore it through univariate, bivariate, and multivariate EDA.
? Engineer better features - apply encoding, feature scaling (standardization and normalization), transformations (log, square-root, Box-Cox), missing-value imputation, and outlier detection.
? Master the core supervised algorithms - Linear and Logistic Regression, SVM, KNN, Naïve Bayes, and Decision Trees, each built up from intuition to math to working Python code.
? Control overfitting and boost accuracy - understand the bias-variance trade-off, apply Ridge/Lasso/Elastic Net regularization, and combine models with bagging, Random Forests, and boosting (XGBoost, LightGBM, CatBoost).
? Evaluate, tune, and go beyond labels - choose the right metrics (precision, recall, F1, ROC-AUC, R²), use cross-validation and hyperparameter tuning while avoiding data leakage, and uncover hidden structure with dimensionality reduction (PCA) and clustering (K-Means, hierarchical).

Who this book is for
This book is for anyone beginning their machine learning journey - undergraduate and graduate students, software developers and engineers, data analysts, aspiring data scientists, and working professionals switching careers. If you know basic Python and high-school math and want to build real intuition alongside practical skills, this book is for you. No advanced mathematics required.

Table of Contents
1. Introduction To Machine Learning
2. End-to-End ML Project
3. Data Ingestion
4. Data Processing
5. Exploratory Data Analysis
6. Feature Engineering - I
7. Feature Engineering - II
8. Linear Models
9. Bias Variance Trade-off

A practical guide to building a modern, GenAI-powered data platform with a Lakehouse foundation, covering MDM, data mesh, AI enablement, streaming pipelines, observability, and cloud-driven architectures for trusted analytics.

Key Features

• Discover characteristics of future-ready platforms - data mesh, automation, & observability
• Design trustworthy data products with contracts, federated governance, and decentralized ownership
• Understand how GenAI accelerates Lakehouse development and enables self-service analytics

Book Description

What you will learn

• Future-ready platforms: data mesh, automation, observability
• Design trusted data products with contracts and governance
• Build Lakehouses with medallion architecture: bronze, silver, gold
• Apply Unity Catalog for governance and endorsed datasets
• Implement MDM using linkages, survivorship, and entity resolution
• Develop real-time and streaming pipelines at scale
• Enable governed self-service analytics for business users
• Use GenAI to generate code with Claude and Databricks Genie

Who this book is for

This book is crafted for aspiring data and AI/ML architects, engineers and analysts starting their data engineering journey and seeking a practical, hands-on guide to building scalable, cloud-driven data platforms. It’s ideal for professionals familiar with PySpark who want to design modern Lakehouse architectures using Delta Lake, while learning MDM, data mesh, AI enablement, streaming pipelines, automation, and data observability. A working knowledge of Python, Spark, and SQL is expected.

Description
Driven by the rise of public hacks and exploits, securing Linux server infrastructures requires robust defense mechanisms. To mitigate modern cyber threats, implementing modern tools like Lynis, ClamAV, and OpenVAS is critical to continuously auditing networks. Fortifying setups using UFW, nftables, and PSAD firewalls, alongside SSH hardening, reduces the attack surface. Additionally, analyzing complex malware through ELF analysis and YARA signatures ensures the integrity of enterprise, cloud, and personal environments.

This book bridges theory and real-world execution by providing a methodical roadmap for proactive defense. It delivers step-by-step instructions, diagrams, and examples of attack types to secure data and applications. IT professionals will learn to deploy resilient internal services, manage incident resolution using rsnapshot or Timeshift backups, and execute a thorough network security assessment.br>
By the end of this book, you will master practical hardening steps to turn vulnerabilities into impenetrable strength. You will possess realistic strategies to create bulletproof systems and enhance site resilience against external threats. Ultimately, you will be fully equipped to protect infrastructure and make your Linux environments completely unbreakable.

Les crises agri-environnementales, de plus en plus prégnantes, soulignent la nécessité de changements de paradigme et d’innovations organisationnelles. Les enjeux qu’elles soulèvent mobilisent une diversité d’acteurs et d’objets naturels (ressources, biodiversité, santé) qui s’inscrivent dans des dynamiques collectives et des temporalités longues — voire infinies lorsqu’il s’agit de préserver des ressources naturelles ou patrimoniales. Dans une perspective de durabilité, se posent alors les questions de l’émergence et de la résilience d’un organizing : comment des processus d’organisation associant une multiplicité d’acteurs et d’objets se construisent-ils et se pérennisent-ils ? Historiquement centrées sur l’entreprise et l’administration, les sciences de gestion apportent un éclairage original sur ces dynamiques d’action collective.S’appuyant sur des études de cas variées (santé animale et végétale, politique de l’eau, gestion multi-usage des territoires…), l’ouvrage interroge aussi les situations d’enquête et la fabrique de l’interdisciplinarité. Il propose une synthèse inédite de connaissances issues de recherches en sciences de gestion et met ainsi en évidence leur apport spécifique à la compréhension et à la gestion des problèmes agri-environnementaux pour éclairer et renouveler les pratiques dans ces domaines. Destiné aux chercheurs, enseignants et étudiants, il intéressera également les professionnels engagés dans des projets de gestion de l’agri-environnement.

In 2006, Chartrand, Johns, McKeon and Zhang introduced the concept of rainbow edge-coloring. A graph G is defined as rainbow connected if every pair of vertices is linked by a path whose edges all receive distinct colors.. The rainbow connection number, rc(G), is the minimum number of colors required to achieve this property. In 2008, Krivelevich and Yuster extended the concept to vertices by introducing the rainbow vertex-connection number, rvc(G). Beyond its role as a natural combinatorial measure, rainbow connection number has applications in secure information transmission and communication network design. 

This book presents the major results on rainbow connection numbers and related graph parameters. It covers upper bounds involving order, minimum degree and degree sum; relationships with radius, diameter, and independence number; results for dense, sparse and random graphs; as well as computational complexity and algorithmic aspects.

Written for graduate students and researchers, this book is of interest to readers working in graph theory, combinatorics, probability, algorithms, and computational complexity.

Description
Cyberattacks continue to evolve in sophistication, frequency, and business impact. Organizations face ransomware attacks, cloud breaches, insider threats, supply chain compromises, AI-driven attacks, and advanced persistent threats that can disrupt operations and damage reputations. Effective incident response is no longer optional; it is a critical business capability.

This book provides a practical approach to cybersecurity incident response, covering threat landscapes, incident handling methodologies, forensic readiness, response playbooks, threat intelligence integration, cloud security incidents, post-incident recovery, and the use of artificial intelligence in modern threat detection and response. Readers will learn how to prepare organizations for cyber incidents, detect threats efficiently, contain and eradicate attacks, preserve forensic evidence, and continuously improve security operations. Real-world examples, industry frameworks, and operational best practices are incorporated throughout the book.

By the end of this book, readers will be equipped to design, implement, and mature incident response programs capable of handling modern cybersecurity challenges while improving organizational resilience and recovery capabilities.

Description
As large language models continue to transform how we build intelligent systems, the ability to integrate proprietary data through vector search and RAG has become essential for creating accurate, contextually-aware applications that go beyond the limitations of pre-trained models

This comprehensive guide takes you from foundational concepts to production-ready implementations of vector databases and RAG systems. Starting with vector semantics and embeddings, you will learn to generate vector representations using neural networks, BERT, and OpenAI models. The book covers popular vector databases including Weaviate and Milvus, teaching you how to implement efficient search algorithms like k-nearest neighbors and hierarchical navigable small worlds. You will build complete RAG pipelines, explore advanced techniques like GraphRAG, and master evaluation frameworks using LlamaIndex. Each chapter includes hands-on Python examples with practical code implementations that demonstrate real-world applications.

By the end of this book, you will have mastered the skills needed to design, build, and evaluate production-grade vector search systems and RAG applications. You will be equipped to enhance LLM applications with private data, implement semantic search at scale, troubleshoot retrieval issues, and solve real-world information retrieval challenges using cutting-edge AI techniques with confidence.

This book presents an innovative integration of Water Quality Engineering with Systems Science and Information Science, offering a comprehensive theoretical framework alongside practical guidance to address the increasingly complex challenges of water quality management. The content is structured into three main parts: (1) Information and Signals in Water Quality Systems; (2) Linear Water Quality Systems; and (3) Nonlinear Water Quality Systems.

Adopting a novel perspective rooted in information space, the book provides a clear and accessible introduction to the fundamental theories and principles of system control in water quality systems. It equips readers with essential methodologies for data acquisition, signal analysis, and the development of precise and intelligent control strategies.

This work is intended as both a textbook and a reference for advanced undergraduate and graduate students in Environmental Engineering and Systems Engineering. It also serves as a valuable resource for researchers, professionals, and engineers working in Information Science and related technological fields.

Description
Quantum computing is rapidly evolving from a theoretical concept into a practical technology, influencing areas such as cybersecurity, optimization, artificial intelligence, and scientific research. As industries explore their potential, there is a growing demand for engineers, developers, and researchers who can understand and apply quantum computing using accessible tools such as Python.

This book is written from a combined perspective of teaching, research, and industry experience, ensuring both conceptual clarity and practical relevance. It introduces core concepts such as qubits, quantum states, gates, and circuits, and then progresses to algorithms such as Grover’s and Shor’s. It also explains quantum hardware, noise, and real-world limitations. You will gain hands-on experience using Qiskit, Cirq, and AWS Braket, along with exposure to advanced topics such as variational algorithms, quantum cryptography, and quantum machine learning, supported by simulation exercises and mini projects.

By the end of this book, readers will be able to design and implement quantum programs, work with modern quantum platforms, and apply quantum concepts to real-world problems with confidence.

Description
Artificial intelligence has evolved beyond chatbots and static decision trees. Enterprise agents today need to be able to see images, understand spoken language, remember context over sessions, and reason through multi-step tasks without human intervention. LangChain has emerged as the leading open-source framework for combining these capabilities into production-ready systems.

This book is a hands-on guide to building multi-modal, context-aware AI agents. Readers start by designing reusable LangChain workflows and selecting the right language models, then move into building multimodal pipelines that handle text, images, and audio together. From there, the book covers vision-enabled agents powered by GPT-4o and CLIP, voice assistants built with Whisper and Azure Speech, and agents with persistent memory that maintain context across sessions. Later chapters tackle emotion-aware interactions, retrieval-augmented generation with hybrid search, and knowledge graph fusion for advanced multi-hop reasoning. The book also explores autonomous agents that execute real-world tasks and provides a practical guide to multi-agent planning, collaboration, and evaluation.

By the end of this book, readers will be equipped to design and deploy production-grade AI agents that handle real-world complexity, agents that see, hear, remember, reason, and act with intelligence and precision.

This book presents a comprehensive overview of recent advances in the study of the Ginzburg-Landau (GL) equations. Organized into five chapters, it introduces the physical background of the GL equations before discussing the existence of global solutions and their asymptotic behavior in one- and higher-dimensional settings. It further examines applications of the GL equations to superconductivity and explores the connections between the GL model and harmonic maps.

Serving as both an introduction and a research reference, the book is intended for researchers in mathematics, physics, mechanics, and related disciplines, as well as university teachers, advanced undergraduate students, and graduate students wishing to deepen their understanding of the theory and applications of the Ginzburg–Landau equations.

Description
AI is powering modern industries across different domains, from recommendations to forecasting, making it a must-have skill. As global AI adoption accelerates, it has become necessary for professionals to understand deeply how to utilize machine learning to build more reliable solutions

The book systematically covers foundational to advanced data science concepts through structured programming implementations. It begins with machine learning fundamentals and exploratory data analysis using NumPy and Pandas, then covers the math behind supervised algorithms like linear regression and unsupervised clustering techniques like K-means. You will master ensemble learning architectures like XGBoost, time series forecasting with FBProphet, automated hyperparameter optimization using the Optuna framework, and imbalanced data corrections via SMOTE. The book concludes with a specialized bonus chapter that breaks down the math behind multi-head self-attention mechanisms and fine-tuning strategies within large language model transformer architectures using the Hugging Face ecosystem.

By the end of this book, readers will be able to move confidently from raw data to working models. They will possess practical skills in data preparation, model building, evaluation, and optimization, giving them the confidence to solve complex, data-driven software engineering problems in real-world scenarios.

Description
AI is rapidly permeating every facet of our lives, fine-tuning the quality of our existence and shaping a better future. Organizations are improving their business performance by leveraging AI in their digital transformation initiatives. At the heart of this fervent global wave are the data scientists, the data engineers, the AI architects and developers, who are infusing AI into applications to solve real-world problems.

This book begins with an understanding of AI, subsequently showing how to apply AI to solve real-world challenges. Each chapter provides several illustrations, code examples, and hands-on exercises to augment further understanding of the technical concepts, preparing the readers to implement right from the very first chapter. The readers also learn how to make their AI-based solutions robust and enterprise-ready. Though the concepts are explained with Java and AI tools in Azure, this could be well applied using other programming languages and other similar cloud environments.

This book will help Java developers and architects quickly ramp up on AI and use the necessary tools to build AI-enabled applications. AI technology stakeholders, administrators, and enthusiasts will learn and understand the concepts and how these are being applied in the real-world.

What you will learn
? Implement language, vision, and speech using cognitive AI.
? Develop text, vector, semantic, and multimodal search capabilities.
? Master generative and document AI for multimodal processing.
? Build multimodal chatbots to handle real-time AI conversations.
? Orchestrate multi-agent systems using Semantic Kernel and MCP.
? Leverage Azure AI, Microsoft Fabric, and AI Foundry.
? Operationalize and secure real-world enterprise AI use cases.

Who this book is for
This book is for Java developers, architects, cloud AI engineers, data scientists, IT administrators, stakeholders, and AI enthusiasts who want to build, design, deploy, and manage AI-enabled applications. It assumes a basic understanding of AI concepts, Azure cloud computing, and Java programming.

Table of Contents
1. Introduction to AI
2. AI in the Cloud
3. Data in AI
4. Language, Vision, Speech
5. Search
6. Generative AI services
7. Document AI
8. Conversational AI
9. AI Agents
10. Security
11. Production
12. Use Cases and Applications

Description
While traditional search engine optimization (SEO) was once the definitive tool for brand visibility, the rise of answer engines and generative models has introduced a notorious shift in consumer behavior. This book provides insights for navigating these changes, ensuring your content remains searchable and relevant in an era where traditional search results are being replaced by direct, AI-generated answers.

The AI Search Playbook provides a comprehensive overview of the emerging strategies necessary to survive this transition. You will learn to master answer engine optimization (AEO) to secure your place in direct AI responses and generative engine optimization (GEO) to influence the outputs of large language models. Key takeaways include techniques for structuring product data for AI consumption, understanding the mechanics of agent-based search, and transitioning your brand’s digital footprint from outdated SEO practices to these sophisticated new discovery frameworks.

By the end of this book, readers will be fully equipped to lead their product data through the AI revolution with confidence and technical competence. You will possess the specialized knowledge required to ensure your products and ideas are not just indexed, but actively found and recommended by the AI agents of tomorrow.

What you will learn
? Understand AI agent product discovery, evaluation, and recommendation mechanisms.
? Mastering SEO, AEO, GEO, and AI-driven product discovery.
? Structure product data, schema markup, and semantic HTML effectively.
? Measure AI visibility using Share of Model and benchmarking.
? Build resilient AI discovery strategies across evolving AI ecosystems.

Who this book is for
This book is for marketing strategists, SEO specialists, content architects, product managers, e-commerce professionals, and digital marketing consultants with a beginner-to-intermediate understanding of search engines and digital discovery. No advanced coding knowledge is required to learn AEO, GEO, and AI-first discovery practices, however, a beginner-to-intermediate grasp of how search engines currently work is necessary.

Table of Contents
1. The Rise of AI Agents
2. Understanding and Mastering AEO
3. GEO Strategies Foundations
4. Structuring Product Data for AI-Driven Recommendations
5. Technical Frameworks for Implementing Agent-ready Catalogs
6. Advanced AEO and Optimizing LLM Citations
7. PXM Evolution and Managing AI Experience
8. Dominating Agentic Shelf with Digital Shelf Analytics
9. Scaling GEO and Automating Visibility Across AI Platforms
10. Future-proofing Brands for the Next AI Shift

Description
Kubernetes has become the leading platform for deploying and managing containerized applications in modern enterprise environments. As organizations continue adopting cloud-native architectures, securing Kubernetes infrastructure and workloads has become a critical requirement. The Certified Kubernetes Security Specialist (CKS) certification validates the practical skills required to secure Kubernetes environments and implement security best practices.

This book is a practical study guide designed to help readers prepare for the CKS exam through hands-on learning and real-world scenarios. It covers cluster hardening, RBAC, service accounts, pod security, supply chain security, runtime security, network policies, logging, monitoring, and policy enforcement. The book includes practical labs, troubleshooting exercises, sample questions, exam-focused scenarios, preparation strategies, and full-length practice papers designed to mirror real certification challenges.

By the end of this book, readers will gain the confidence to secure Kubernetes environments and handle real-world security challenges. DevOps engineers, platform engineers, cloud architects, and security engineers will develop practical skills needed to succeed in the CKS certification and beyond.

Ce livre présente de manière simple et motivée les notions de géométrie riemannienne nécessaires pour appréhender les fondements géométriques de la relativité générale. Il est issu d’un cours donné à la Société Astronomique de France en 2025. Son ambition est de fournir au lecteur un exposé mathématique précis et rigoureux, mais sans s’attarder sur les détails techniques : l’absence de certaines démonstrations (pour lesquelles des références précises sont données) est compensée par des justifications heuristiques des objets introduits. 
En ce sens, ce cours sera un « guide de géométrie différentielle » pour les étudiants mathématiciens, leur permettant de découvrir les fondements théoriques de la relativité, source de recherches mathématiques importantes. Il séduira également les étudiants physiciens souhaitant approfondir les bases mathématiques de leurs cours de relativité générale. Une bonne compréhension des objets mathématiques ici présentés leur facilitera l’acquisition d’une maîtrise technique des outils de la géométrie différentielle et de la relativité générale, tout en posant des bases solides pour aborder des aspects théoriques plus avancés.

Riches d’une biodiversité exceptionnelle, les océans assurent de nombreux services essentiels à l’être humain, parmi lesquels la production d’oxygène, la régulation du climat ou l’approvisionnement alimentaire. Ces ressources majeures pour l’avenir de la planète sont toutefois soumises à des pressions croissantes, qui interrogent nos connaissances actuelles sur ces milieux. 

Que sait-on réellement des océans et des changements qui s’y opèrent ? La Lune est-elle la seule à agir sur les marées ? Les coraux vivent-ils aussi dans les eaux froides ? De nouvelles espèces de mammifères marins continuent encore d’être identifiées de nos jours. Quant à la surexploitation des ressources halieutiques, elle n’est pas forcément irréversible. 

En apportant un éclairage scientifique aux idées fausses souvent associées aux océans, cet ouvrage explore leurs propriétés physiques, la diversité du vivant qu’ils abritent, les ressources qu’ils fournissent et les pressions qui les affectent.

This book provides a comprehensive introduction to the fundamentals of aeronautical science and technology, guiding readers from the origins of flight to the latest developments in aerospace engineering. Structured in six main parts, it covers the history of aviation, basic aerodynamics, flight principles, aircraft propulsion systems, aircraft structures, and aircraft instruments and navigation, while also presenting selected recent technological advances in the field. Combining historical perspective with engineering fundamentals, the book offers clear explanations, practical insights, and numerous illustrations to help readers understand the principles that underpin modern aviation and aerospace systems.

Designed primarily for undergraduate students in aeronautical and aerospace engineering, this textbook is particularly well suited to introductory courses in flight and aviation science. It provides a solid foundation in key subjects such as aerodynamics, flight mechanics, stability and control, propulsion, aircraft structures, helicopter fundamentals, and astronautics. The accessible presentation also makes it a valuable resource for aviation enthusiasts and readers seeking a structured introduction to the field.