Study

Deep Reinforcement Learning (Part 3)

Berkeley CS 285 Review My solution to the homework Deep Reinforcement Learning (Part 1) Deep Reinforcement Learning (Part 2) ...

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

CSE547: Machine Learning for Big Data 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 ...