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).
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.
發表於2025-01-31
Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition 2025 pdf epub mobi 電子書 下載
第一部分寫scikit的還行,後麵第二部分關於神經網絡部分,原文寫的就亂,很多術語代碼該解釋的不解釋,寫的稀裏糊塗,翻譯更是糊塗,完全當不起5星。 舉個例子,第13章330頁最下麵,“最後一層是不言而喻的:放棄正則化”,翻譯的人你給我齣來,解釋一下什麼是放棄正則化,那tm...
評分第一部分寫scikit的還行,後麵第二部分關於神經網絡部分,原文寫的就亂,很多術語代碼該解釋的不解釋,寫的稀裏糊塗,翻譯更是糊塗,完全當不起5星。 舉個例子,第13章330頁最下麵,“最後一層是不言而喻的:放棄正則化”,翻譯的人你給我齣來,解釋一下什麼是放棄正則化,那tm...
評分https://github.com/it-ebooks/hands-on-ml-zh ==========================================================================================================================================================
評分tensorflow的官方文檔寫的比較亂,這本書的齣現,恰好拯救瞭一批想入門tf,又看不進去官方文檔的人。行文非常棒,例子豐富,有助於工程實踐。這本書上提到瞭一些理論,簡單形象;但是,理論不是此書的重點,也不應是此書的重點。這本書對於機器學習小白十分友好,讀完瞭也就差...
評分================================================== https://github.com/DeqianBai/Hands-on-Machine-Learning ================================================== 自己翻譯的版本,還在更新,打開一個Jupyter 文件就可以一邊學習理論,一遍進行操作驗證 原書的代碼示例部...
圖書標籤: 機器學習 tensorflow Python 計算機科學 AI deeplearning keras MachineLearning
我認為這是當前最好的機器學習實踐書籍,不僅有實例而且還講明瞭原理,非常難得的好書。
評分可以很快讀完的科普書,最後一次翻開是在麵試後迴看聚類數量的選擇。
評分可以很快讀完的科普書,最後一次翻開是在麵試後迴看聚類數量的選擇。
評分這2年作者又看瞭不少paper,很多地方甚至都改口瞭,Keras作者的DL的第二版預計2020年春天齣版
評分機器學習實戰利器,值得一讀再讀。一刷,2020-01-06,Great。
Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition 2025 pdf epub mobi 電子書 下載