Here is a link to event page. Machine Learning: A Probabilistic Perspective Notes - ML textbook with an emphasis on describing concepts with relation to probability. Elements of Statistical Learning ...
Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. Subjects include supervised ...
In this book you will learn how to align on ML strategies in a team setting, as well as how to set up development (dev) sets and test sets. Recommendations for how to set up dev/test sets have been ...
The lectures should be self-contained, but these books should help you, especially if you would like to dive deeper. Requires prereq courses of CSCI 2820 or APPM 3310 or MATH 2130 or CSCI 3022 or APPM ...
Privacy considerations in machine learning Differential privacy techniques for machine learning Privacy-preserving synthetic data generation Privacy-enhancing ...
into digital textbooks can enhance learning experiences. Published in the Proceedings of Machine Learning Research, this work envisions a future where static course materials transform into ...
Chris is the author of two highly cited and widely adopted machine learning text books: Neural Networks for Pattern Recognition (1995) and Pattern Recognition and Machine Learning (2006). He has also ...