Deep Reinforcement Learning (Part 3)
Berkeley CS 285 Review My solution to the homework Deep Reinforcement Learning (Part 1) Deep Reinforcement Learning (Part 2) ...
Study
Deep Reinforcement Learning (Part 2)
Berkeley CS 285 Review My solution to the homework Deep Reinforcement Learning (Part 1) Deep Reinforcement Learning (Part 3) ...
Deep Reinforcement Learning (Part 1)
Berkeley CS 285 Review My solution to the homework Deep Reinforcement Learning (Part 2) Deep Reinforcement Learning (Part 3) ...
Nonlinear System
ME 583 Review. Based on Nonlinear Systems (Hassan K. Khalil) book. ...
Matrix Derivatives
Notes on doing derivatives w.r.t. matrix/vector. Based on matrix vector derivatives for machine learning.pdf Another good resource is matrixcookbook.pdf ...
Machine Learning
Machine Learning notes. Coursera Andrew Ng Machine Learning. My solution Stanford CS231n Convolutional Neural Networks for Visual Recognition. My solution ...
Convex Optimization
AA/EE/ME 578 Review ...
Machine Learning for Big Data
CSE 547 Review ...
Algorithms I
This is a review of the Princeton University Algorithms, Part I course offered on Coursera. For the second part of the course, see Algorithms II. My solutions to the programming assignments are available on GitHub. ...
Linear Algebra Review
From ME 510 & AMATH 584 ...