The slides under talks/ are javascript and html-based using reveal.js and d3.js. They can be viewed online via github pages:
- On Traditional Machine Learning The workshops are provided as jupyter notebooks, which can be served as reveal.js presentations.
git clone git@github.com:AdrianoDee/course_ml4hep.git
An (incomplete) list of interesting books:
- Christopher M. Bishop. Pattern Recognition and Machine Learning
- Trevor Hastie, Robert Tibshirani, and Jerome Friedman. The Elements of Statistical Learning.
- J. Han, M. Kamber, J. Pei. Data Mining: Concepts and Techniques
- O. Behnke, K. Kröninger, G. Scott, T. Schörner-Sadenius. Data Analysis in High Energy Physics: A Practical Guide to Statistical Methods
- I. Goodfellow, Y. Bengio, A. Courville. Deep Learning (Adaptive Computation and Machine Learning)
- R. S. Sutton, and A. G. Barto. Reinforcement Learning: An Introduction