Machine Learning and Pattern Recognition

AI3011 | Spring 2025

Recommended Resources

Books

• Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition by Aurélien Géron, 2019, O'Reilly Media Inc
  
  ISBN: 9781492032649





• Understanding Machine Learning from Theory to Algorithms by Shai Shalev-Shwartz and Shai Ban-David, 2014, Cambridge University Press
  
  ISBN: 9781107298019





• Pattern Recognition and Machine Learning by Christopher M. Bishop, 2006, Springer New York
  
  ISBN: 9780387310732





• Introduction to Machine Learning, Third Edition by Ethem Alpaydin, 2014, The MIT Press
  
  ISBN: 9780262028189





• Pattern Classification, 2nd Edition by Richard O. Duda, Peter E. Hart, David G. Stork, 2000, Wiley
  
  ISBN: 9780471056690





• Data Mining and Analysis: Fundamental Concepts and Algorithms by Mohammed J. Zaki, 2014, Cambridge University Press
  
  ISBN: 9780511810114





• Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy by Cathy O'Neil, 2016, Crown Publishing Group
  
  ISBN: 9780553418811





• The Deep Learning Revolution by Terrence J. Sejnowski, 2018, The MIT Press
  
  ISBN: 9780262038034

Blogs and Online Resources

• Professor Sebastian Raschka’s courses on Machine Learning and Deep Learning


• A curated list of AI and Machine Learning resources


• Machine learning articles from Analytics Vidhya

Videos

• Machine Learning videos by Prof. Andrew Ng


• Machine Learning videos by Prof. Sudeshna Sarkar


• Machine Learning videos by Prof. G. C. Nandi


• Understanding Machine Learning by Prof. Shai Ben-David


• Neural Networks videos by 3blue1brown YouTube channel

Datasets

• Kaggle


• Govt. of India Data Repository


• UC Irvine Machine Learning Repository