| 書目名稱 | Hands-on Scikit-Learn for Machine Learning Applications |
| 副標(biāo)題 | Data Science Fundame |
| 編輯 | David Paper |
| 視頻video | http://file.papertrans.cn/424/423993/423993.mp4 |
| 概述 | Introduces the popular Scikit-Learn library for machine learning algorithms in Python.Provides examples in Python that are made specifically for data science.Teaches principles of machine learning tha |
| 圖書封面 |  |
| 描述 | Aspiring data science professionals can learn the Scikit-Learn library along with the fundamentals of machine learning with this book. The book combines the Anaconda Python distribution with the popular Scikit-Learn library to demonstrate a wide range of supervised and unsupervised machine learning algorithms. Care is taken to walk you through the principles of machine learning through clear examples written in Python that you can try out and experiment with at home on your own machine..All applied math and programming skills required to master the content are covered in this book. In-depth knowledge of object-oriented programming is not required as working and complete examples are provided and explained. Coding examples are in-depth and complex when necessary. They are also concise, accurate, and complete, and complement the machine learning concepts introduced. Working the examples helps to build the skills necessary to understand and apply complexmachine learning algorithms..Hands-on Scikit-Learn for Machine Learning Applications. is an excellent starting point for those pursuing a career in machine learning. Students of this book will learn the fundamentals that are a prerequi |
| 出版日期 | Book 2020 |
| 關(guān)鍵詞 | Scikit-Learn; Anaconda Distribution; Python; NumPy; Machine Learning; Data Science; Classifiers; Confusion |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4842-5373-1 |
| isbn_softcover | 978-1-4842-5372-4 |
| isbn_ebook | 978-1-4842-5373-1 |
| copyright | David Paper 2020 |
|Archiver|手機(jī)版|小黑屋|
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