Resources for Biologists
Tensorflow tutorials
Recommended:
- Tensorflow tutorials (Link)
- Francis Chollet’s tensorflow 2 + keras tutorial
(Code)
- Interpretability analysis with Tensorflow 2.0 (Link)
Other resources:
- Coursera TensorFlow 2 for Deep Learning Specialization by Imperial College London
(Video)
Linear algebra
Linear algebra courses
Linear Algebra course at MIT with Gilbert Strang
(Website,
Video)
ML math book
- Mathematics for Machine Learning by Deisenroth et al. (Link)
Machine Learning
ML courses
- Andrew Ng’s Intro to Machine Learning Course at Stanford
(Website,
Video)
Classic ML books
- Pattern recognition and machine learning by Christopher Bishop (Link, Code, Solutions)
- Machine Learning: A Probabilistic Interpretation by Kevin Murphy (Link)
Deep Learning
DL courses
- Convolutional Neural Networks for Visual Recognition Course at Stanford
(Website,
Video)
- Designing, Visualizing and Understanding Deep Neural Networks at UC Berkeley by Sergey Levine
(Website,
Video)
DL books
- Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow (Book, Link)
Comp Biology courses
- Shirley Liu’s Introduction to Computational Biology and bioinformatics Course at Harvard
(Website, Video)