Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition pdf epub mobi txt 電子書下載2025

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Aurélien Géron is a machine learning consultant and trainer. A former Googler, he led YouTube's video classification team from 2013 to 2016. He was also a founder and CTO of Wifirst (a leading Wireless ISP in France) from 2002 to 2012, and a founder and CTO of two consulting firms -- Polyconseil (telecom, media and strategy) and Kiwisoft (machine learning and data privacy).

出版者:O′Reilly

作者:Aurelien Geron

出品人:

頁數:600

译者:

出版時間:2019-10-11

價格:GBP 55.99

裝幀:Paperback

isbn號碼:9781492032649

叢書系列:

圖書標籤:

機器學習
tensorflow
Python
計算機科學
AI
deeplearning
keras
MachineLearning

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Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data.

The updated edition of this best-selling book uses concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow 2—to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. Practitioners will learn a range of techniques that they can quickly put to use on the job. Part 1 employs Scikit-Learn to introduce fundamental machine learning tasks, such as simple linear regression. Part 2, which has been significantly updated, employs Keras and TensorFlow 2 to guide the reader through more advanced machine learning methods using deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started.

NEW FOR THE SECOND EDITION:Updated all code to TensorFlow 2Introduced the high-level Keras APINew and expanded coverage including TensorFlow’s Data API, Eager Execution, Estimators API, deploying on Google Cloud ML, handling time series, embeddings and more

With Early Release ebooks, you get books in their earliest form—the author's raw and unedited content as he or she writes—so you can take advantage of these technologies long before the official release of these titles. You'll also receive updates when significant changes are made, new chapters are available, and the final ebook bundle is released.

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讀後感

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明年才出版，结合这两者的树很顺应时代需求啊，希望能出中文版，虽然英文读起来更好，但是为了效率，学习技术还是中文的来得更快些。

評分☆☆☆☆☆

tensorflow的官方文档写的比较乱，这本书的出现，恰好拯救了一批想入门tf，又看不进去官方文档的人。行文非常棒，例子丰富，有助于工程实践。这本书上提到了一些理论，简单形象；但是，理论不是此书的重点，也不应是此书的重点。这本书对于机器学习小白十分友好，读完了也就差...

評分☆☆☆☆☆

================================================== https://github.com/DeqianBai/Hands-on-Machine-Learning ================================================== 自己翻译的版本，还在更新，打开一个Jupyter 文件就可以一边学习理论，一遍进行操作验证原书的代码示例部...

評分☆☆☆☆☆

比一些照着pakcage的API tutorial抄出来的书姿势水平不知道高到哪里去了。个人认为这本书最精华的部分在于Appendix B 机器学习项目清单，基本上工业界做一套Machine Learning解决方案顺着这个checklist问一遍自己就够了，需要Presentation的场合按照这个结构来组织也非常合适...