Best Reference Books for Machine Learning
List of "Best Reference Books for Machine Learning" compiled based on Amazon book reviews by experts. These books are used by students of top institutes, universities, colleges and professionals. Please feel free to suggest any other book on this topic using the comment section below.
- Machine Learning by Tom M. MitchellMcGraw Hill Education (Number of pages: 432)
- Introduction to Machine Learning with Python: A Guide for Data Scientists by Andreas MullerShroff/O'Reilly (Number of pages: 392)
- Building Machine Learning Systems with Python by Willi Richert,Luis Pedro Coelho,Jonathan Chaffer,Karl SwedbergPackt Publishing Limited (Number of pages: 290)
- Introduction to Machine Learning 3RD Edition by ETHEM ALPAYDINPHI LEARNING PVT. LTD-NEW DELHI (Number of pages: 612)
- Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurelien GeronShroff/O'Reilly (Number of pages: 568)
- Pattern Recognition and Machine Learning (Information Science and Statistics) by Christopher M. BishopSpringer (Number of pages: 738)
- Artificial Intelligence 3e: A Modern Approach by RussellPearson Education India (Number of pages: 1164)
- Machine Learning (in Python and R) For Dummies by Luca Massaron John Paul MuellerWiley (Number of pages: 432)
- Machine Learning in Action by Peter HarringtonDreamtech Press (Number of pages: 380)
- Machine Learning for Big Data: Hands-On for Developers and Technical Professionals by Jason BellWiley (Number of pages: 404)
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