BOOKS - Python Machine Learning By Example
Python Machine Learning By Example - Liu Yuxi 2024 PDF Packt Publishing BOOKS
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Python Machine Learning By Example
Author: Liu Yuxi
Year: 2024
Pages: 519
Format: PDF
File size: 31.9 Мб
Language: ENG



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Python Machine Learning By Example Introduction The book "Python Machine Learning By Example" by Sebastian Raschka provides a comprehensive guide to machine learning using Python, covering various aspects of the field, from basic concepts to advanced techniques. The author's approach is based on practical examples, making it easy for readers to understand and apply the concepts presented in the book. This review will provide an overview of the book's content, highlighting its strengths and weaknesses, and offering suggestions for readers who want to learn more about machine learning using Python. Overview of the Book The book is divided into 12 chapters, each focusing on a specific aspect of machine learning. The first chapter introduces the concept of machine learning and its importance in today's world, while the second chapter covers the basics of Python programming, providing a solid foundation for the rest of the book. The following chapters delve into various machine learning algorithms, including linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), and neural networks. The book also discusses more advanced topics such as clustering, dimensionality reduction, and deep learning. Strengths of the Book 1. Practical Examples: The book's strength lies in its practical approach, with numerous examples that help readers understand complex concepts in a simple and intuitive way. Each chapter includes exercises and projects that allow readers to apply their knowledge and reinforce their understanding. 2. Easy-to-Understand Language: The author uses clear and concise language, making it accessible to readers with little or no prior knowledge of machine learning or Python programming. 3.
Python Machine arning By Example Введение Книга «Python Machine arning By Example» Себастьяна Рашки представляет собой исчерпывающее руководство по машинному обучению с использованием Python, охватывающее различные аспекты области, от основных концепций до передовых техник. Авторский подход базируется на практических примерах, облегчая читателям понимание и применение представленных в книге концепций. В этом обзоре будет представлен обзор содержания книги, подчеркивающий ее сильные и слабые стороны, а также предложения для читателей, которые хотят узнать больше о машинном обучении с использованием Python. Обзор книги Книга разделена на 12 глав, каждая из которых посвящена определенному аспекту машинного обучения. Первая глава вводит понятие машинного обучения и его значение в современном мире, в то время как вторая глава охватывает основы программирования на Python, обеспечивая прочную основу для остальной части книги. В следующих главах рассматриваются различные алгоритмы машинного обучения, включая линейную регрессию, логистическую регрессию, деревья решений, случайные леса, машины опорных векторов (SVM) и нейронные сети. В книге также обсуждаются более продвинутые темы, такие как кластеризация, уменьшение размерности и глубокое обучение. Сильные стороны Книги 1. Практические примеры: Сила книги заключается в ее практическом подходе, с многочисленными примерами, которые помогают читателям понять сложные концепции простым и интуитивным способом. Каждая глава включает в себя упражнения и проекты, которые позволяют читателям применять свои знания и укреплять их понимание. 2. Простой для понимания язык: автор использует ясный и лаконичный язык, что делает его доступным для читателей, практически не знающих машинного обучения или программирования на Python. 3.
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