Machine learning for beginners / Miles Sterling.

By: Sterling, Miles [author. ]Material type: TextTextPublisher: London, United Kingdom : Vintage Press Ltd., c2025Edition: First editionDescription: viii, 264 pages : color illustration ; 24 cmContent type: text Media type: unmediated Carrier type: volume ISBN: 9781836831648 [hardbound] Subject(s): Machine learning | Artificial intelligence | Computer algorithms
Contents:
Contents: 1. Introduction to machine learning -- 2. Types of machine learning -- 3. Key concepts and terminology -- 4. Machine learning algorithms -- 5. Data collection and preprocessing -- 6. Introduction to python for machine learning -- 7. Exploratory data analysis (EDA) -- 8. AI and machine learning in eLearning -- 9. Data mining techniques.
Summary: "In embarking on the journey of understanding machine learning, I found myself both captivated and overwhelmed by the vastness of the field. It's a realm where mathematics, computer science, and real-world applications converge, transforming how we interact with technology and make decisions. This book, "Machine Learning for Beginners," is designed to bridge that gap for those who are just starting out. Machine learning is not merely about algorithms and data; it's about discovering patterns, making predictions, and enabling machines to learn from experience. My aim is to demystify these concepts, breaking them down into digestible parts. Each chapter builds upon the last, offering practical examples and hands-on exercises that encourage exploration and experimentation. As I delved into this subject, I realized the importance of a solid foundation. The book starts with essential principles, guiding readers through the fundamental concepts before diving into more complex topics. It is structured to be accessible, ensuring that even those without a technical background can grasp the material. Throughout this work, I Iemphasize emphasize the t importance of a growth mindset. The landscape of machine learning is ever-evolving, and embracing curiosity and resilience is key to mastering its intricacies. Whether you aspire to enhance your career, fuel your creativity, or simply understand the technology shaping our world, this book is your starting point. In this exploration of machine learning, my hope is to inspire a sense of wonder and possibility. By the end, you will not only have gained knowledge but also the confidence to continue your journey in this exciting field. Let's dive in and unlock the potential of machine learning together —Miles Sterling." --Preface
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006.31 St45 2025 (Browse shelf) Available 3UCBL000029701

Includes bibliographical references and index.

Contents: 1. Introduction to machine learning -- 2. Types of machine learning -- 3. Key concepts and terminology -- 4. Machine learning algorithms -- 5. Data collection and preprocessing -- 6. Introduction to python for machine learning -- 7. Exploratory data analysis (EDA) -- 8. AI and machine learning in eLearning -- 9. Data mining techniques.

"In embarking on the journey of understanding machine learning, I found myself both captivated and overwhelmed by the vastness of the field. It's a realm where mathematics, computer science, and real-world applications converge, transforming how we interact with technology and make decisions. This book, "Machine Learning for Beginners," is designed to bridge that gap for those who are just starting out.

Machine learning is not merely about algorithms and data; it's about discovering patterns, making predictions, and enabling machines to learn from experience. My aim is to demystify these concepts, breaking them down into digestible parts. Each chapter builds upon the last, offering practical examples and hands-on exercises that encourage exploration and experimentation.

As I delved into this subject, I realized the importance of a solid foundation. The book starts with essential principles, guiding readers through the fundamental concepts before diving into more complex topics. It is structured to be accessible, ensuring that even those without a technical background can grasp the material.

Throughout this work, I Iemphasize emphasize the t importance of a growth mindset. The landscape of machine learning is ever-evolving, and embracing curiosity and resilience is key to mastering its intricacies. Whether you aspire to enhance your career, fuel your creativity, or simply understand the technology shaping our world, this book is your starting point.

In this exploration of machine learning, my hope is to inspire a sense of wonder and possibility. By the end, you will not only have gained knowledge but also the confidence to continue your journey in this exciting field. Let's dive in and unlock the potential of machine learning together —Miles Sterling." --Preface

Adult

Purchased Ortega, Eric College of Computer Studies Computer Science

Text in English

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