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2025-03-24
Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition 2025 pdf epub mobi 電子書 下載
https://github.com/it-ebooks/hands-on-ml-zh ==========================================================================================================================================================
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...
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...
評分挺不錯的,推薦做ML的同學都拿來看看,一定能學到不少東西,尤其是接觸沒多久的 不足之處是例子還是稍顯不足,我個人更想要Kaggle真題解析 一些我比較喜歡的地方如下 1. 2-3章適閤所有剛接觸數據科學的同學 第2章 California housing(加州區域房價)的例子非常實際,能學到很...
圖書標籤: 機器學習 tensorflow Python 計算機科學 AI deeplearning keras MachineLearning
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【書.2020-01】博大精深的學科,感覺是必讀的。
評分相比keras入門的那本,這本有一些中級的技術以及近兩年的先進結構。我就是來找ReNet的實現的
評分【書.2020-01】博大精深的學科,感覺是必讀的。
評分ML啓濛,全代碼的比那種全公式的看著舒服很多,看完瞭有監督部分,水水項目也就足夠瞭。
Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition 2025 pdf epub mobi 電子書 下載