Machine Learning Books

Here are some must-read books on machine learning:

• Introduction to Machine Learning by Alfred V. Aho, John E. Hopcroft, and Jeffrey D. Ullman

  • A comprehensive introduction to the field of machine learning, covering algorithms, statistical models, and more.
  • Read more

• Pattern Recognition and Machine Learning by Christopher M. Bishop

  • A detailed and mathematically rigorous book on pattern recognition and machine learning.
  • Read more

• Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville

  • The definitive book on deep learning, covering the theory and practice of deep neural networks.
  • Read more

• Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig

  • A widely used textbook on artificial intelligence, providing a solid foundation for understanding the field.
  • Read more

If you are looking for Chinese resources:

• 机器学习 by 周志华

  • An introduction to machine learning with a focus on Chinese language and culture.
  • Read more

• 深度学习 by 邱锡鹏

  • A comprehensive guide to deep learning, with a strong emphasis on practical applications.
  • Read more

• 模式识别与机器学习 by 李航

  • A detailed book on pattern recognition and machine learning, written in Chinese.
  • Read more

For more information on machine learning, check out our Machine Learning Resources page.