| 书目名称 | Mastering Machine Learning with Python in Six Steps | | 副标题 | A Practical Implemen | | 编辑 | Manohar Swamynathan | | 视频video | | | 概述 | Covers basic to advanced topics in an easy step-oriented manner.Concise on theory, strong focus on practical and hands-on approach.Explores advanced topics, such as Hyper-parameter tuning, deep natura | | 图书封面 |  | | 描述 | .Master machine learning with Python in six steps and explore fundamental to advanced topics, all designed to make you a worthy practitioner. .This book’s approach is based on the “Six degrees of separation” theory, which states that everyone and everything is a maximum of six steps away. .Mastering Machine Learning with Python in Six Steps. presents each topic in two parts: theoretical concepts and practical implementation using suitable Python packages. .You’ll learn the fundamentals of Python programming language, machine learning history, evolution, and the system development frameworks. Key data mining/analysis concepts, such as feature dimension reduction, regression, time series forecasting and their efficient implementation in Scikit-learn are also covered. Finally, you’ll explore advanced text mining techniques, neural networks and deep learning techniques, and their implementation. . .All the code presented in the book will be available in the form of iPython notebooks to enable you to try out these examples and extend them to your advantage..What You‘ll Learn.Examine the fundamentals of Python programming language.Review machine Learning history and evolution.Understand | | 出版日期 | Book 20171st edition | | 关键词 | Machine Learning; Python; Scikit-Learn; Model Tuning; Text Mining; Neural Networks; Deep Learning | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4842-2866-1 | | isbn_ebook | 978-1-4842-2866-1 | | copyright | Manohar Swamynathan 2017 |
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发表于 2025-3-21 19:25:33
