Python machine learning

A gentle journey through the mathematics of neural networks, and making your own using the Python computer language. Neural networks are a key element of deep learning and artificial intelligence, whi

Control your machine learning algorithms using test-driven development to achieve quantifiable milestonesAbout This BookBuild smart extensions to pre-existing features at work that can help maximize t

If you have experience with the Python language and are interested in getting started with electronics, then BeagleBone Black is the perfect platform for you and this book will provide you with the in

Efficient Learning Machines explores all the major topics of machine learning, including big data, knowledge discovery, classifications, genetic algorithms, neural networking, kernel methods, and gami

This books teaches fundamental programming concepts using the powerful, yet easy to learn, Python programming language. Python is a cross-platform language used by organizations such as Google and NAS

An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning

Operations Research uses a balanced combination of theory, applications and computations to help you learn the basics of operating research (OR). It focuses on algorithmic and practical implementation of OR techniques. Easy-to-understand numerical examples explain often difficult math concepts, helping you grasp the foundational idea without getting stuck on complex theorems or notations. Full case studies and math-free anecdotes show how algorithms are used in real-life applications.The 11th Edition introduces analytics, artificial intelligence, and machine learning topics that strengthen and streamline the decision-making processes involved in OR. New stories, 3 new chapters, new case studies and sections provide an up-to-date introduction to the field of OR.

A concise but informative overview of AI ethics and policy.Artificial intelligence, or AI for short, has generated a staggering amount of hype in the past several years. Is it the game-changer it's been cracked up to be? If so, how is it changing the game? How is it likely to affect us as customers, tenants, aspiring homeowners, students, educators, patients, clients, prison inmates, members of ethnic and sexual minorities, and voters in liberal democracies? Authored by experts in fields ranging from computer science and law to philosophy and cognitive science, this book offers a concise overview of moral, political, legal and economic implications of AI. It covers the basics of AI's latest permutation, machine learning, and considers issues such as transparency, bias, liability, privacy, and regulation.Both business and government have integrated algorithmic decision support systems into their daily operations, and the book explores the implications for our lives as citizens. For exam

Elementary Linear Algebra: Applications Version, 12th Edition, gives an elementary treatment of linear algebra that is suitable for a first course for undergraduate students. The classic treatment of linear algebra presents the fundamentals in the clearest possible way, examining basic ideas by means of computational examples and geometrical interpretation. It proceeds from familiar concepts to the unfamiliar, from the concrete to the abstract. Readers consistently praise this outstanding text for its expository style and clarity of presentation. In this edition, a new section has been added to describe the applications of linear algebra in emerging fields such as data science, machine learning, climate science, geomatics, and biological modeling. New exercises have been added with special attention to the expanded early introduction to linear transformations and new examples have been added, where needed, to support the exercise sets. Calculus is not a prerequisite, but there are clea

Discover a practical, streamlined approach to systems development that focuses on the latest developments with Tilley's Systems Analysis and Design, Cengage International Edition, 13th, and MindTap digital resources. Real examples clearly demonstrate both traditional and emerging approaches to systems analysis and design, including object-oriented and agile methods. You also study emerging technologies such as artificial intelligence (AI), machine learning (ML), cloud computing and cybersecurity. Meaningful projects, insightful assignments and both online and printed exercises emphasize the critical thinking and IT skills that are most important in today's dynamic, business-related environment.

多智能體強化學習(Multi-Agent Reinforcement Learning, MARL)是機器學習中的一個領域，研究多個智能體如何在共享環境中學習最優的交互方式。這一領域在現代生活中有著廣泛的應用，包括自動駕駛、多機器人工廠、自動化交易和能源網絡管理等。 本書是一部系統闡述多智能體強化學習理論與技術的權威著作，清晰而嚴謹地介紹了MARL的模型、解決方案概念、算法思想、技術挑戰以及現代方法。書中首先介紹了該領域的基礎知識，包括強化學習理論和算法的基礎、交互式博弈模型、博弈中的不同解決方案概念以及支撐MARL研究的算法思想。隨後，書中詳細介紹了利用深度學習技術的現代MARL算法，涵蓋集中訓練與分散執行、價值分解、參數共享和自博弈等思想。本書還附帶了一個用Python編寫的MARL代碼庫，其中包括自包含且易於閱讀的MARL算法實現。 本書技術內容以易於理解的語言解釋，並通過大量示例進行說明，既為初學者闡明了MARL的概念，也為專業的讀者提供了高層次的見解。

《強化學習基礎、原理與應用》循序漸進地講解了使用Python語言實現強化學習的核心算法開發的知識，內容涵蓋了數據處理、算法、大模型等知識，並通過具體實例的實現過程演練了各個知識點的使用方法和使用流程。《強化學習基礎、原理與應用》共分為17章，主要內容包括強化學習基礎、馬爾可夫決策過程、蒙特卡洛方法、Q-learning與貝爾曼方程、時序差分學習和SARSA算法、DQN算法、DDQN算法、競爭DQN算法、REINFORCE算法、Actor-Critic算法、PPO算法、TRPO算法、連續動作空間的強化學習、值分布式算法、基於模型的強化學習、多智能體強化學習實戰：Predator-Prey 遊戲及自動駕駛系統。本書內容簡潔而不失技術深度，以極簡的文字介紹了複雜的案例，易於閱讀和理解。《強化學習基礎、原理與應用》適用於已經瞭解Python語言基礎語法的讀者，想進一步學習強化學習、機器學習、深度學習及相關技術的讀者，還可作為大專院校相關專業的師生用書和培訓機構的教材使用。

Twins Scarlett and Thomas have been learning about the Maya at school. They even had a go at making hot chocolate from cacao beans. When Grandad falls ill, the twins know what the perfect cure will be – hot chocolate! They nervously borrow Grandad’s time machine and travel back to the time of the Mayas. Scarlett pretends to be a god, and gets taken in by the royal family. Thomas is not quite so lucky, and ends up playing for his life in a brutal Mayan ball game. Watch out, Thomas, if you lose, you might be sacrificed to the gods! How far would you go to find the best hot chocolate?