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学习建议

本仓库为网络收集资料且自己学习所用,不用做任何商业用途,若有侵犯到相关版权,请联系删除。

1. 书籍列表

1.1 机器学习

  1. 《机器学习》(又名《西瓜书》)周志华,PDF

    《南瓜书》DataWhale,PDF

  2. 《统计学习方法》李航,第一版第二版

  3. 《Pattern Recognition and Machine Learning》(PRML,模式识别与机器学习)Bishop,原版PDF中文PDF

  4. 《Machine Learning in Action》(机器学习实战)Peter Harrington ,原版PDF中文PDF

1.2 深度学习

  1. 《Deep Learning》(深度学习,又名花书)Ian Goodfellow,原版PDF中文PDF

  2. 《动手学深度学习》(d2l,Dive into Deep Learning,也叫深入深度学习)李沐,英文PDF中文PDF

  3. 《神经网络与深度学习》(nndl,蒲公英书)邱锡鹏,PDF

  4. 《Hands-On Machine Learning with Scikit-Learn Keras, and TensorFlow》Aurélien Géron,原版PDF中文PDF

  5. 《Deep Learning with Python》François Chollet,原版PDF中文PDF

1.3 强化学习

  1. 《Reinforcement Learning: An Introduction》(强化学习简介,强化学习导论,强化学习(第二版))Sutton,英文PDF中文PDF(扫描版)

  2. 《深度强化学习》(DRL,也叫猫书)王树森,V1草稿PDFGitHub草稿PDF

  3. 《Deep Reinforcement Learning Hands-On: Apply modern RL methods to practical problems of chatbots, robotics, discrete optimization, web automation, and more, 2nd Edition》Maxim Lapan,原版PDF中文PDF

  4. 《Easy-RL》(也叫蘑菇书)DataWhale,PDF

  5. 《深入浅出强化学习:原理入门》郭宪 方勇纯,PDF

  6. 《深度强化学习:基础、研究与应用》董豪,PDF

  7. 《深度强化学习核心算法与应用》陈世勇, 苏博览,杨敬文,PDF

  8. 《强化学习》威宁, 赵地等译,PDF

  9. 《强化学习》邹伟, 鬲玲, 刘昱杓,PDF

  10. 《强化学习入门:从原理到实践.pdf》叶强, 闫维新, 黎斌,PDF

  11. 《统计强化学习:现代机器学习方法》杉山将,PDF

等等。

许可证(LICENSE)

本仓库内容为网络资源且自己学习所用,不用做任何商业用途,故本仓库所有资源继承与原资源的许可证,若有相关许可疑问,以原资源许可证为准。若本仓库有资源侵犯相关产权,请联系删除。

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