Resources for Biologists

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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)

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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)

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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)

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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)

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Comp Biology courses

• Shirley Liu’s Introduction to Computational Biology and bioinformatics Course at Harvard (Website, Video)