NEW FOUNDATION OF ARTIFICIAL INTELLIGENCE

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This book lays a new foundation toward achieving artificial self-intelligence by future machines such as intelligent vehicles. Its chapters provide a broad coverage to the three key modules behind the design and development of intelligent vehicles for the ultimate purpose of actively ensuring driving safety as well as preventing accidents from all possible causes. Self-contained and unified in presentation, the book explains in details the fundamental solutions of vehicle's perception, vehicle's decision-making, and vehicle's action-taking in a pedagogic order. Besides the fundamental knowledge and concepts of intelligent vehicle's perception, decision and action, this book includes a comprehensive set of real-life application scenarios in which intelligent vehicles will play a major role or contribution. These case studies of real-life applications will help motivate students to learn this exciting subject. With concise and simple explanations, and boasting a rich set of graphical illustrations, the book is an invaluable source for both undergraduate and postgraduate courses, on artificial intelligence, intelligent vehicle, and robotics, which are offered in automotive engineering, computer engineering, electronic engineering, and mechanical engineering. In addition, the book will help strengthen the knowledge and skills of young researchers who want to venture into the research and development of artificial self-intelligence for intelligent vehicles of the future.

Introduction to Artificial Intelligence and Machine Learning (1版)

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【簡介】 Helps students unlock the power of AI and Machine Learning to achieve business success and future-proof their careersArtificial intelligence and machine learning are transforming the modern workplace, making AI literacy a critical skill for business professionals. Introduction to Artificial Intelligence and Machine Learning equips students with essential AI/ML knowledge and practical skills, enabling them to leverage cutting-edge technology in today’s data-driven world. With an engaging and accessible approach, this textbook ensures that students--regardless of technical background--gain a working knowledge of AI/ML systems. Concise, easy-to-digest chapters blend foundational concepts with real-world applications to help students develop the expertise needed to implement AI/ML solutions across industries. For instructors, the textbook offers flexible teaching methodologies, whether focusing on conceptual discussions, light technology applications, or full AI/ML projects. With a clear business perspective and a strong emphasis on AI governance and deployment, the textbook prepares students to navigate the future of AI in the workplace with confidence. Helping students build a solid foundation in key concepts while exploring strategic implementation and ethical considerations, Introduction to Artificial Intelligence and Machine Learning is ideal for undergraduate and graduate students in business, engineering, and healthcare programs taking courses such as Business Analytics, Information Systems, and AI Strategy. AN INTERACTIVE, MULTIMEDIA LEARNING EXPERIENCEThis textbook includes access to an interactive, multimedia e-text. Icons throughout the print book signal corresponding digital content in the e-text. Video Clips created by the author complement the text and engage students more deeply with AI/ML concepts and applications.Interactive Figures and Charts are integrated throughout the enhanced e-text to provide engaging visual representations of the material.Interactive Questions appear in each chapter of the enhanced e-text, providing students with immediate feedback to strengthen learning.

Certiport ITS Artificial Intelligence 人工智慧核心能力國際認證應考攻略 (1版)

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【簡介】 　　Information Technology Specialist（ITS）是由Pearson VUE／Certiport推出符合產業趨勢的資訊科技認證，涵蓋IT資訊技術、資料庫、軟體研發、新興科技四大領域，透過 ITS 各項認證指標訓練，可驗證考生是否確實掌握業界所需與具備雇主所需的 IT 技能，幫助考生為未來職涯做好準備。  　　 　　本書整理了 ITS Artificial Intelligence 人工智慧 認證考科綱要所涵蓋的資訊技術與電腦技能，考生可透過精進學習本書各章節重點內容，迅速掌握應考方向。  【目錄】 Chapter 01 AI 問題定義  確認要透過人工智慧解決的問題  對問題進行分類  確認解決問題所需的專業領域  建立安全計劃  確保適當使用人工智慧  選擇透明度和驗證活動  Chapter 02 數據收集、處理和工程  選擇數據收集方式  評估數據品質  確保數據具有代表性  確認資源需求  將數據轉換為適當格式  為人工智慧模型選擇特徵  進行特徵工程  確定訓練和測試數據集  記錄數據決策  Chapter 03 人工智慧演算法與模型  考慮特定演算法的適用性  使用選定的演算法進行模型訓練  進行實驗後選擇特定的模型，避免過度工程  敘述數據故事  評估模型表現  尋找演算法中可能的偏見來源  評估模型敏感度  確認是否符合法規要求  獲得利害關係人的批准  Chapter 04 應用整合與部署  對客戶進行培訓  計劃應對模型在生產環境中的挑戰  設計生產流程，包括應用程式整合  提供對人工智慧解決方案的支援  Chapter 05 生產環境中的維護與監控  進行監督和監控  評估商業影響  測量 AI 對個人和社群的影響  處理來自用戶的反饋  定期考慮改進或停用的可能性  Chapter 06 模擬試題  ITS 資訊科技專家國際專業認證  Artificial Intelligence  人工智慧核心能力  Chapter 07 ITS 資訊科技專家國際認證原廠認證應考資訊  ITS 資訊科技專家國際認證  如何參加 Certiport ITS 國際認證考試  考前準備事項  帳號註冊  考後成績查詢與列印電子證書