{"title":"SOFTWARE ENGINEERING","description":null,"products":[{"product_id":"fundamentals-of-software-architecture-a-modern-engineering-approach-by-mark-richards","title":"Fundamentals of Software Architecture: A Modern Engineering Approach by Mark Richards","description":"\u003cp\u003e\u003cspan\u003eSalary surveys worldwide regularly place software architect in the top 10 best jobs, yet no real guide exists to help developers become architects. Until now. This updated edition provides a comprehensive overview of software architecture's many aspects, with five new chapters covering the latest insights from the field. Aspiring and existing architects alike will examine architectural characteristics, architectural patterns, component determination, diagramming architecture, governance, data, generative AI, team topologies, and many other topics.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eMark Richards and Neal Ford—hands-on practitioners who have taught software architecture classes professionally for years—focus on architecture principles that apply across all technology stacks. You'll explore software architecture in a modern light, taking into account all the innovations of the past decade.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eThis book examines:\u003c\/span\u003e\u003c\/p\u003e\n\u003cul class=\"a-unordered-list a-vertical\"\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003eArchitecture styles and patterns\u003c\/span\u003e\u003cspan\u003e: Microservices, modular monoliths, microkernels, layered architectures, and many more\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003eComponents\u003c\/span\u003e\u003cspan\u003e: Identification, coupling, cohesion, partitioning, and granularity\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003eSoft skills\u003c\/span\u003e\u003cspan\u003e: Effective team management, collaboration, business engagement models, negotiation, presentations, and more\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003eModernity\u003c\/span\u003e\u003cspan\u003e: Engineering practices and operational approaches that have changed radically in the past few years, including cloud considerations and generative AI\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003eArchitecture as an engineering discipline\u003c\/span\u003e\u003cspan\u003e: Repeatable results, metrics, and concrete valuations that add rigor to software architecture\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"Booksdomain","offers":[{"title":"Default Title","offer_id":54099478249583,"sku":null,"price":400.0,"currency_code":"MAD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0742\/6696\/8175\/files\/81L2JlIRjQL._SY522__2.jpg?v=1787511987"},{"product_id":"software-architecture-the-hard-parts-modern-trade-off-analyses-for-distributed-architectures-by-neal-ford","title":"Software Architecture: The Hard Parts: Modern Trade-Off Analyses for Distributed Architectures by Neal Ford","description":"\u003cdiv class=\"a-expander-content a-expander-partial-collapse-content a-expander-content-expanded\"\u003e\n\u003cp\u003e\u003cspan\u003eThere are no easy decisions in software architecture. Instead, there are many hard parts--difficult problems or issues with no best practices--that force you to choose among various compromises. With this book, you'll learn how to think critically about the trade-offs involved with distributed architectures.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eArchitecture veterans and practicing consultants Neal Ford, Mark Richards, Pramod Sadalage, and Zhamak Dehghani discuss strategies for choosing an appropriate architecture. By interweaving a story about a fictional group of technology professionals--the Sysops Squad--they examine everything from how to determine service granularity, manage workflows and orchestration, manage and decouple contracts, and manage distributed transactions to how to optimize operational characteristics, such as scalability, elasticity, and performance.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eBy focusing on commonly asked questions, this book provides techniques to help you discover and weigh the trade-offs as you confront the issues you face as an architect.\u003c\/span\u003e\u003c\/p\u003e\n\u003cul class=\"a-unordered-list a-vertical\"\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eAnalyze trade-offs and effectively document your decisions\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eMake better decisions regarding service granularity\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eUnderstand the complexities of breaking apart monolithic applications\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eManage and decouple contracts between services\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eHandle data in a highly distributed architecture\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eLearn patterns to manage workflow and transactions when breaking apart applications\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e","brand":"Booksdomain","offers":[{"title":"Default Title","offer_id":54099490439279,"sku":null,"price":400.0,"currency_code":"MAD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0742\/6696\/8175\/files\/51oVT2PQgPL._SY445_SX342_FMwebp.webp?v=1787512152"},{"product_id":"design-patterns-elements-of-reusable-object-oriented-software","title":"Design Patterns: Elements of Reusable Object-Oriented Software","description":"\u003cp\u003e\u003cspan\u003eCapturing a wealth of experience about the design of object-oriented software, four top-notch designers present a catalog of simple and succinct solutions to commonly occurring design problems. Previously undocumented, these 23 patterns allow designers to create more flexible, elegant, and ultimately reusable designs without having to rediscover the design solutions themselves.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cbr\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eThe authors begin by describing what patterns are and how they can help you design object-oriented software. They then go on to systematically name, explain, evaluate, and catalog recurring designs in object-oriented systems. With Design Patterns as your guide, you will learn how these important patterns fit into the software development process, and how you can leverage them to solve your own design problems most efficiently.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cbr\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eEach pattern describes the circumstances in which it is applicable, when it can be applied in view of other design constraints, and the consequences and trade-offs of using the pattern within a larger design. All patterns are compiled from real systems and are based on real-world examples. Each pattern also includes code that demonstrates how it may be implemented in object-oriented programming languages like C++ or Smalltalk.\u003c\/span\u003e\u003c\/p\u003e","brand":"Booksdomain","offers":[{"title":"Default Title","offer_id":54099500073071,"sku":null,"price":389.0,"currency_code":"MAD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0742\/6696\/8175\/files\/81YsHe4woRL._SY522.jpg?v=1787512279"},{"product_id":"reinforcement-learning-second-edition-an-introduction-adaptive-computation-and-machine-learning-series","title":"Reinforcement Learning, second edition: An Introduction (Adaptive Computation and Machine Learning series)","description":"\u003cp\u003e\u003cspan class=\"a-text-bold\"\u003eThe significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eReinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In \u003c\/span\u003e\u003cspan class=\"a-text-italic\"\u003eReinforcement Learning\u003c\/span\u003e\u003cspan\u003e, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eLike the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.\u003c\/span\u003e\u003c\/p\u003e","brand":"Booksdomain","offers":[{"title":"Default Title","offer_id":54099507576943,"sku":null,"price":599.0,"currency_code":"MAD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0742\/6696\/8175\/files\/41dDV91Eu3L._SY445_SX342_FMwebp.webp?v=1787512394"},{"product_id":"build-a-reasoning-model-from-scratch","title":"Build a Reasoning Model (From Scratch)","description":"\u003cp\u003e\u003cspan\u003eThis book is a practical guide to understanding how modern reasoning-oriented LLMs work by building their core methods step by step. The book tells a clear engineering story: start with a conventional pre-trained LLM, learn how text generation works, build reliable evaluation tools, improve reasoning through inference-time methods, then move into training-based approaches such as reinforcement learning and distillation.\u003cbr\u003e\u003cbr\u003eThe progression is deliberate. Early chapters establish the baseline model and explain text generation, KV caching, and evaluation with math verifiers. The middle chapters show how reasoning can be improved without changing model weights, using chain-of-thought prompting, sampling, self-consistency, response scoring, and self-refinement. Later chapters move to changing the model itself through reinforcement learning with verifiable rewards, GRPO improvements, format rewards, and finally distillation from stronger reasoning models into smaller ones.\u003cbr\u003e\u003cbr\u003eThe book is especially useful because it implements the core methods from scratch rather than treating them as black-box library calls. Readers see how self-consistency, self-refinement, Best-of-N, and training-based methods actually work, including their cost and latency trade-offs. It also discusses common failure modes, including cases where refinement can make answers worse. Difficult concepts such as softmax, temperature, and top-p sampling are clarified with code-linked explanations and diagrams, and visual workflows make pipelines and scoring methods easier to follow.\u003cbr\u003e\u003cbr\u003eReading the book feels like following a guided technical build rather than a loose survey of AI topics. Each concept is introduced because the project now needs it. Diagrams, roadmaps, code listings, exercises, and repeated workflow summaries help readers stay oriented through advanced material. This structure reflects \u003c\/span\u003e\u003cspan class=\"a-text-bold\"\u003eSebastian Raschka’s\u003c\/span\u003e\u003cspan\u003e professional strength: explaining complex machine learning topics by making every detail concrete and showing exactly where each section fits in the larger story. He does not treat mechanisms like evaluation, log-probabilities, KL regularization, or distillation as isolated abstractions; he connects them to the goal of making reasoning models understandable and implementable.\u003cbr\u003e\u003cbr\u003ePhysically and organizationally, the book has eight chapters and seven substantial appendixes. That design keeps the main narrative focused while moving supporting material like references, exercise solutions, model source code, larger models, batching, evaluation alternatives, and chat interfaces into ordered appendixes. The result is a logically flowing book that remains hands-on, navigable, and technically deep without constantly interrupting the central build.\u003cbr\u003e\u003cbr\u003e\u003c\/span\u003e\u003cspan class=\"a-text-bold\"\u003eWhat's inside\u003c\/span\u003e\u003cspan\u003e\u003cbr\u003e\u003cbr\u003e• From-scratch implementations of core LLM reasoning improvements\u003cbr\u003e• Verifier-based evaluation methods\u003cbr\u003e• RL with automatic verifiers for mathematics tasks\u003cbr\u003e\u003cbr\u003e\u003c\/span\u003e\u003cspan class=\"a-text-bold\"\u003eAbout the reader\u003c\/span\u003e\u003cspan\u003e\u003cbr\u003e\u003cbr\u003eFor readers who know Python and have some knowledge of machine learning.\u003cbr\u003e\u003cbr\u003e\u003c\/span\u003e\u003cspan class=\"a-text-bold\"\u003eAbout the author\u003c\/span\u003e\u003cspan\u003e\u003cbr\u003e\u003cbr\u003e\u003c\/span\u003e\u003cspan class=\"a-text-bold\"\u003eSebastian Raschka\u003c\/span\u003e\u003cspan\u003e is an LLM Research Engineer with over a decade of experience. He is the author of the bestselling book \u003c\/span\u003e\u003cspan class=\"a-text-italic\"\u003eBuild a Large Language Model (From Scratch).\u003c\/span\u003e\u003cspan\u003e\u003cbr\u003e\u003cbr\u003e\u003c\/span\u003e\u003cspan class=\"a-text-bold\"\u003eTable of Contents\u003c\/span\u003e\u003cspan\u003e\u003cbr\u003e\u003cbr\u003e1 Understanding reasoning models\u003cbr\u003e2 Generating text with a pretrained LLM\u003cbr\u003e3 Evaluating reasoning models\u003cbr\u003e4 Improving reasoning with inference-time scaling\u003cbr\u003e5 Inference-time scaling via self-refinement\u003cbr\u003e6 Training reasoning models with reinforcement learning\u003cbr\u003e7 Improving GRPO for reinforcement learning\u003cbr\u003e8 Distilling reasoning models for efficient reasoning\u003cbr\u003eA References and further reading\u003cbr\u003eB Exercise solutions\u003cbr\u003eC Qwen3 LLM source code\u003cbr\u003eD Using larger LLMs\u003cbr\u003eE Batching and throughput-oriented execution\u003cbr\u003eF Common approaches to model evaluation\u003cbr\u003eG Building a chat interface\u003c\/span\u003e\u003c\/p\u003e","brand":"Booksdomain","offers":[{"title":"Default Title","offer_id":54099521634415,"sku":null,"price":497.0,"currency_code":"MAD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0742\/6696\/8175\/files\/71Ahb2iunzL._SY466.jpg?v=1787512500"},{"product_id":"build-a-large-language-model-from-scratch-by-sebastian-raschka","title":"Build a Large Language Model (From Scratch) by Sebastian Raschka","description":"\u003cdiv class=\"a-expander-content a-expander-partial-collapse-content a-expander-content-expanded\"\u003e\n\u003cspan class=\"a-text-italic\"\u003eBuild a Large Language Model (from Scratch)\u003c\/span\u003e\u003cspan\u003e teaches you how to:\u003c\/span\u003e\n\u003cul class=\"a-unordered-list a-vertical\"\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003ePlan and code all the parts of an LLM\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003ePrepare a dataset suitable for LLM training\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eFine-tune LLMs for text classification and with your own data\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eUse human feedback to ensure your LLM follows instructions\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eLoad pretrained weights into an LLM\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cspan\u003e\u003cbr\u003e\u003c\/span\u003e\u003cspan class=\"a-text-italic\"\u003eBuild a Large Language Model (from Scratch)\u003c\/span\u003e\u003cspan\u003e takes you inside the AI black box to tinker with the internal systems that power generative AI. As you work through each key stage of LLM creation, you’ll develop an in-depth understanding of how LLMs work, their limitations, and their customization methods. Your LLM can be developed on an ordinary laptop, and used as your own personal assistant.\u003cbr\u003e\u003cbr\u003e\u003c\/span\u003e\u003cspan class=\"a-text-bold\"\u003eAbout the technology\u003c\/span\u003e\u003cspan\u003e\u003cbr\u003e\u003cbr\u003ePhysicist Richard P. Feynman reportedly said, “I don’t understand anything I can’t build.” Based on this same powerful principle, bestselling author Sebastian Raschka guides you step by step as you build a GPT-style LLM that you can run on your laptop. This is an engaging book that covers each stage of the process, from planning and coding to training and fine-tuning.\u003cbr\u003e\u003cbr\u003e\u003c\/span\u003e\u003cspan class=\"a-text-bold\"\u003eAbout the book\u003c\/span\u003e\u003cspan\u003e\u003cbr\u003e\u003cbr\u003e\u003c\/span\u003e\u003cspan class=\"a-text-italic\"\u003eBuild a Large Language Model (From Scratch)\u003c\/span\u003e\u003cspan\u003e is a practical and eminently-satisfying hands-on journey into the foundations of generative AI. Without relying on any existing LLM libraries, you’ll code a base model, evolve it into a text classifier, and ultimately create a chatbot that can follow your conversational instructions. And you’ll really understand it because you built it yourself!\u003cbr\u003e\u003cbr\u003e\u003c\/span\u003e\u003cspan class=\"a-text-bold\"\u003eWhat's inside\u003c\/span\u003e\n\u003cul class=\"a-unordered-list a-vertical\"\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003ePlan and code an LLM comparable to GPT-2\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eLoad pretrained weights\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eConstruct a complete training pipeline\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eFine-tune your LLM for text classification\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eDevelop LLMs that follow human instructions\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cspan\u003e\u003cbr\u003e\u003c\/span\u003e\u003cspan class=\"a-text-bold\"\u003eAbout the reader\u003c\/span\u003e\u003cspan\u003e\u003cbr\u003e\u003cbr\u003eReaders need intermediate Python skills and some knowledge of machine learning. The LLM you create will run on any modern laptop and can optionally utilize GPUs.\u003cbr\u003e\u003cbr\u003e\u003c\/span\u003e\u003cspan class=\"a-text-bold\"\u003eAbout the author\u003c\/span\u003e\u003cspan\u003e\u003cbr\u003e\u003cbr\u003e\u003c\/span\u003e\u003cspan class=\"a-text-bold\"\u003eSebastian Raschka\u003c\/span\u003e\u003cspan\u003e is a Staff Research Engineer at Lightning AI, where he works on LLM research and develops open-source software.\u003cbr\u003e\u003cbr\u003eThe technical editor on this book was \u003c\/span\u003e\u003cspan class=\"a-text-bold\"\u003eDavid Caswell\u003c\/span\u003e\u003cspan\u003e.\u003cbr\u003e\u003cbr\u003e\u003c\/span\u003e\u003cspan class=\"a-text-bold\"\u003eTable of Contents\u003c\/span\u003e\u003cspan\u003e\u003cbr\u003e\u003cbr\u003e1 Understanding large language models\u003cbr\u003e2 Working with text data\u003cbr\u003e3 Coding attention mechanisms\u003cbr\u003e4 Implementing a GPT model from scratch to generate text\u003cbr\u003e5 Pretraining on unlabeled data\u003cbr\u003e6 Fine-tuning for classification\u003cbr\u003e7 Fine-tuning to follow instructions\u003cbr\u003eA Introduction to PyTorch\u003cbr\u003eB References and further reading\u003cbr\u003eC Exercise solutions\u003cbr\u003eD Adding bells and whistles to the training loop\u003cbr\u003eE Parameter-efficient fine-tuning with LoRA\u003c\/span\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"a-expander-header a-expander-partial-collapse-header\"\u003e\u003c\/div\u003e","brand":"Booksdomain","offers":[{"title":"Default Title","offer_id":54099556663407,"sku":null,"price":490.0,"currency_code":"MAD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0742\/6696\/8175\/files\/71eljkULtwL._SY466.jpg?v=1787512982"},{"product_id":"introduction-to-algorithms-fourth-edition","title":"Introduction to Algorithms, fourth edition","description":"\u003cp\u003e\u003cspan class=\"a-text-bold\"\u003eA comprehensive update of the leading algorithms text, with new material on matchings in bipartite graphs, online algorithms, machine learning, and other topics.\u003c\/span\u003e\u003cspan\u003e\u003cbr\u003e\u003cbr\u003eSome books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. \u003c\/span\u003e\u003cspan class=\"a-text-italic\"\u003eIntroduction to Algorithms\u003c\/span\u003e\u003cspan\u003e uniquely combines rigor and comprehensiveness. It covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers, with self-contained chapters and algorithms in pseudocode. Since the publication of the first edition, \u003c\/span\u003e\u003cspan class=\"a-text-italic\"\u003eIntroduction to Algorithms\u003c\/span\u003e\u003cspan\u003e has become the leading algorithms text in universities worldwide as well as the standard reference for professionals. This fourth edition has been updated throughout.\u003cbr\u003e\u003cbr\u003e\u003c\/span\u003e\u003cspan\u003e\u003cu\u003eNew for the fourth edition\u003c\/u\u003e\u003c\/span\u003e\u003cspan\u003e\u003cbr\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cul class=\"a-unordered-list a-vertical\"\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eNew chapters on matchings in bipartite graphs, online algorithms, and machine learning\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cul class=\"a-unordered-list a-vertical\"\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eNew material on topics including solving recurrence equations, hash tables, potential functions, and suffix arrays\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cul class=\"a-unordered-list a-vertical\"\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003e140 new exercises and 22 new problems\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cul class=\"a-unordered-list a-vertical\"\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eReader feedback–informed improvements to old problems\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cul class=\"a-unordered-list a-vertical\"\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eClearer, more personal, and gender-neutral writing style\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cul class=\"a-unordered-list a-vertical\"\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eColor added to improve visual presentation\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cul class=\"a-unordered-list a-vertical\"\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eNotes, bibliography, and index updated to reflect developments in the field\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cul class=\"a-unordered-list a-vertical\"\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eWebsite with new supplementary material\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e \u003c\/p\u003e","brand":"Booksdomain","offers":[{"title":"Default Title","offer_id":54149508956271,"sku":null,"price":850.0,"currency_code":"MAD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0742\/6696\/8175\/files\/61Mw06x2XcL._SY425__1.jpg?v=1787856015"},{"product_id":"computer-systems-a-programmers-perspective","title":"Computer Systems: A Programmer's Perspective","description":"\u003cp\u003e\u003cspan class=\"a-text-bold a-text-italic\"\u003eComputer systems: A Programmer’s Perspective\u003c\/span\u003e\u003cspan\u003e explains the underlying elements common among all computer systems and how they affect general application performance. Written from the programmer’s perspective, this book strives to teach readers how understanding basic elements of computer systems and executing real practice can lead them to create better programs.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eSpanning across computer science themes such as hardware architecture, the operating system, and systems software, the \u003c\/span\u003e\u003cspan class=\"a-text-bold\"\u003eThird Edition\u003c\/span\u003e\u003cspan\u003e serves as a comprehensive introduction to programming. This book strives to create programmers who understand all elements of computer systems and will be able to engage in any application of the field--from fixing faulty software, to writing more capable programs, to avoiding common flaws. It lays the groundwork for readers to delve into more intensive topics such as computer architecture, embedded systems, and cybersecurity.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eThis book focuses on systems that execute an x86-64 machine code, and recommends that programmers have access to a Linux system for this course. Programmers should have basic familiarity with C or C++.\u003c\/span\u003e\u003c\/p\u003e","brand":"Booksdomain","offers":[{"title":"Default Title","offer_id":54149511643247,"sku":null,"price":950.0,"currency_code":"MAD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0742\/6696\/8175\/files\/41i7hOoZLDL._SX342_SY445_FMwebp.webp?v=1787856163"},{"product_id":"code-the-hidden-language-of-computer-hardware-and-software-by-charles-petzold","title":"Code: The Hidden Language of Computer Hardware and Software by Charles Petzold","description":"\u003cp\u003e\u003cspan class=\"a-text-bold\"\u003eThe classic guide to how computers work, updated with new chapters and interactive graphics\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan class=\"a-text-italic\"\u003e\"For me, Code was a revelation. It was the first book about programming that spoke to me. It started with a story, and it built up, layer by layer, analogy by analogy, until I understood not just the Code, but the System. Code is a book that is as much about Systems Thinking and abstractions as it is about code and programming. Code teaches us how many unseen layers there are between the computer systems that we as users look at every day and the magical silicon rocks that we infused with lightning and taught to think.\"\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan class=\"a-text-italic\"\u003e- Scott Hanselman, Partner Program Director, Microsoft, and host of Hanselminutes\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eComputers are everywhere, most obviously in our laptops and smartphones, but also our cars, televisions, microwave ovens, alarm clocks, robot vacuum cleaners, and other smart appliances. Have you ever wondered what goes on inside these devices to make our lives easier but occasionally more infuriating?\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eFor more than 20 years, readers have delighted in Charles Petzold's illuminating story of the secret inner life of computers, and now he has revised it for this new age of computing. Cleverly illustrated and easy to understand, this is the book that cracks the mystery. You'll discover what flashlights, black cats, seesaws, and the ride of Paul Revere can teach you about computing, and how human ingenuity and our compulsion to communicate have shaped every electronic device we use.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eThis new expanded edition explores more deeply the bit-by-bit and gate-by-gate construction of the heart of every smart device, the central processing unit that combines the simplest of basic operations to perform the most complex of feats. Petzold's companion website, CodeHiddenLanguage.com, uses animated graphics of key circuits in the book to make computers even easier to comprehend.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eIn addition to substantially revised and updated content, new chapters include:\u003c\/span\u003e\u003c\/p\u003e\n\u003cul class=\"a-unordered-list a-vertical\"\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eChapter 18: Let's Build a Clock!\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eChapter 21: The Arithmetic Logic Unit\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eChapter 22: Registers and Busses\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eChapter 23: CPU Control Signals\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eChapter 24: Jumps, Loops, and Calls\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eChapter 28: The World Brain\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cspan\u003eFrom the simple ticking of clocks to the worldwide hum of the internet, Code reveals the essence of the digital revolution.\u003c\/span\u003e\u003c\/p\u003e","brand":"Booksdomain","offers":[{"title":"Default Title","offer_id":54149513773167,"sku":null,"price":399.0,"currency_code":"MAD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0742\/6696\/8175\/files\/61Hc-9h_-XL._SY522.jpg?v=1787856314"},{"product_id":"structure-and-interpretation-of-computer-programs-2nd-edition-mit-electrical-engineering-and-computer-science","title":"Structure and Interpretation of Computer Programs - 2nd Edition (MIT Electrical Engineering and Computer Science)","description":"\u003cp\u003e\u003cspan class=\"a-text-italic\"\u003eStructure and Interpretation of Computer Programs\u003c\/span\u003e\u003cspan\u003e has had a dramatic impact on computer science curricula over the past decade. This long-awaited revision contains changes throughout the text. There are new implementations of most of the major programming systems in the book, including the interpreters and compilers, and the authors have incorporated many small changes that reflect their experience teaching the course at MIT since the first edition was published. A new theme has been introduced that emphasizes the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming and lazy evaluation, and nondeterministic programming. There are new example sections on higher-order procedures in graphics and on applications of stream processing in numerical programming, and many new exercises. In addition, all the programs have been reworked to run in any Scheme implementation that adheres to the IEEE standard.\u003c\/span\u003e\u003c\/p\u003e","brand":"Booksdomain","offers":[{"title":"Default Title","offer_id":54149520785519,"sku":null,"price":499.0,"currency_code":"MAD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0742\/6696\/8175\/files\/41hjJoVmqoL._SY445_SX342_FMwebp__1.webp?v=1787856444"},{"product_id":"llm-engineers-handbook-master-the-art-of-engineering-large-language-models-from-concept-to-production","title":"LLM Engineer's Handbook: Master the art of engineering large language models from concept to production","description":"\u003cp\u003e\u003cspan\u003eArtificial intelligence has undergone rapid advancements, and Large Language Models (LLMs) are at the forefront of this revolution. This LLM book offers insights into designing, training, and deploying LLMs in real-world scenarios by leveraging MLOps best practices. The guide walks you through building an LLM-powered twin that’s cost-effective, scalable, and modular. It moves beyond isolated Jupyter notebooks, focusing on how to build production-grade end-to-end LLM systems.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eThroughout this book, you will learn data engineering, supervised fine-tuning, and deployment. The hands-on approach to building the LLM Twin use case will help you implement MLOps components in your own projects. You will also explore cutting-edge advancements in the field, including inference optimization, preference alignment, and real-time data processing, making this a vital resource for those looking to apply LLMs in their projects.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eBy the end of this book, you will be proficient in deploying LLMs that solve practical problems while maintaining low-latency and high-availability inference capabilities. Whether you are new to artificial intelligence or an experienced practitioner, this book delivers guidance and practical techniques that will deepen your understanding of LLMs and sharpen your ability to implement them effectively.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch4\u003e\u003cspan\u003eWhat you will learn\u003c\/span\u003e\u003c\/h4\u003e\n\u003cul class=\"a-unordered-list a-vertical\"\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eImplement robust data pipelines and manage LLM training cycles\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eCreate your own LLM and refine it with the help of hands-on examples\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eGet started with LLMOps by diving into core MLOps principles such as orchestrators and prompt monitoring\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003ePerform supervised fine-tuning and LLM evaluation\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eDeploy end-to-end LLM solutions using AWS and other tools\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eDesign scalable and modularLLM systems\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eLearn about RAG applications by building a feature and inference pipeline\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch4\u003e\u003cspan\u003eWho this book is for\u003c\/span\u003e\u003c\/h4\u003e\n\u003cp\u003e\u003cspan\u003eThis book is for AI engineers, NLP professionals, and LLM engineers looking to deepen their understanding of LLMs. Basic knowledge of LLMs and the Gen AI landscape, Python and AWS is recommended. Whether you are new to AI or looking to enhance your skills, this book provides comprehensive guidance on implementing LLMs in real-world scenarios\u003c\/span\u003e\u003c\/p\u003e\n\u003ch4\u003e\u003cspan\u003eTable of Contents\u003c\/span\u003e\u003c\/h4\u003e\n\u003col class=\"a-ordered-list a-vertical\"\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eUnderstanding the LLM Twin Concept and Architecture\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eTooling and Installation\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eData Engineering\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eRAG Feature Pipeline\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eSupervised Fine-Tuning\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eFine-Tuning with Preference Alignment\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eEvaluating LLMs\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eInference Optimization\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eRAG Inference Pipeline\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eInference Pipeline Deployment\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eMLOps and LLMOps\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ol\u003e","brand":"Booksdomain","offers":[{"title":"Default Title","offer_id":54149527240815,"sku":null,"price":400.0,"currency_code":"MAD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0742\/6696\/8175\/files\/71C2Wlmta-L._SY466__1.jpg?v=1787856587"},{"product_id":"hands-on-machine-learning-with-scikit-learn-keras-and-tensorflow-concepts-tools-and-techniques-to-build-intelligent-systems-by-aurelien-geron","title":"Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurélien Géron","description":"\u003cp\u003e\u003cspan\u003eThrough a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eWith this updated third edition, author Aurélien Géron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003cul class=\"a-unordered-list a-vertical\"\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eUse Scikit-learn to track an example ML project end to end\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eExplore several models, including support vector machines, decision trees, random forests, and ensemble methods\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eExploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eDive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, autoencoders, diffusion models, and transformers\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eUse TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"Booksdomain","offers":[{"title":"Default Title","offer_id":54173930061935,"sku":null,"price":699.0,"currency_code":"MAD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0742\/6696\/8175\/files\/51SLnCjnj-L._SY445_SX342_FMwebp__1.webp?v=1788042176"}],"url":"https:\/\/domainbooksma.com\/collections\/software-engineering.oembed","provider":"Booksdomain","version":"1.0","type":"link"}