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Название: Just Enough Data Science and Machine Learning: Essential Tools and Techniques
Автор: Mark Levene, Martyn Harris
Издательство: Addison-Wesley Professional/Pearson Education
Год: 2025
Страниц: 224
Язык: английский
Формат: epub
Размер: 10.1 MB
An accessible introduction to applied Data Science and Machine Learning, with minimal math and code required to master the foundational and technical aspects of Data Science. In Just Enough Data Science and Machine Learning, authors Mark Levene and Martyn Harris present a comprehensive and accessible introduction to Data Science. It allows the readers to develop an intuition behind the methods adopted in both Data Science and Machine Learning, which is the algorithmic component of Data Science involving the discovery of patterns from input data. This book looks at Data Science from an applied perspective, where emphasis is placed on the algorithmic aspects of Data Science and on the fundamental statistical concepts necessary to understand the subject. The book begins by exploring the nature of Data Science and its origins in basic statistics. The authors then guide readers through the essential steps of Data Science, starting with exploratory data analysis using visualisation tools. The book is packed with practical examples and real-world data sets throughout to reinforce the concepts. All examples are supported by Python code external to the reading material to keep the book timeless.
Автор: Mark Levene, Martyn Harris
Издательство: Addison-Wesley Professional/Pearson Education
Год: 2025
Страниц: 224
Язык: английский
Формат: epub
Размер: 10.1 MB
An accessible introduction to applied Data Science and Machine Learning, with minimal math and code required to master the foundational and technical aspects of Data Science. In Just Enough Data Science and Machine Learning, authors Mark Levene and Martyn Harris present a comprehensive and accessible introduction to Data Science. It allows the readers to develop an intuition behind the methods adopted in both Data Science and Machine Learning, which is the algorithmic component of Data Science involving the discovery of patterns from input data. This book looks at Data Science from an applied perspective, where emphasis is placed on the algorithmic aspects of Data Science and on the fundamental statistical concepts necessary to understand the subject. The book begins by exploring the nature of Data Science and its origins in basic statistics. The authors then guide readers through the essential steps of Data Science, starting with exploratory data analysis using visualisation tools. The book is packed with practical examples and real-world data sets throughout to reinforce the concepts. All examples are supported by Python code external to the reading material to keep the book timeless.