Awesome_ML

Stuffs about Machine Learning.
List some interesting resources to study Machine Learning here.
Mostly are posts and surveys, but also include interesting discussion and interdisciplinary works.
Welcome to contribute(PR) and please give a reason why it's interesting.

Table of Contents

Awesome_ML

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Mathematics Basics

Physics Basics

QC for ML: A Survey, a great survey
UIUC: QC and Shor's Algorithm
IIT: Seminar on Quantum Computing, a brief intro to quantum computing
UT: Quantum Machine Learning(YouTube)

Tensor Theory

MPI: Introduction to Tensors
Tensor Network
Tensors.net
Tensor Decompositions and Applications
TN VS ML, connection between TN and ML

Machine Learning Basics

To be an expert in a specified field of ML, you must lay a solid foundation of the basics:

Computer Vision

Natural Language Processing

Distributed Deep Learning

Ring AllReduce, a straightforward tutorial for beginners: share reduce and share only

Control Theory and Reinforcement Learning

UIUC: Calculus of Variations and Optimal Control Theory
Cool Things in Optimal Control and Physics
HJB Equations & Stochastic Differential Equations, details about Hamiltonian v.s. Bellman
OpenAI: Spinning Up
Stanford: Reinforcement Learning An Introduction
UCB: CS294 Deep Reinforcement Learning
强化学习线路, containing some flaws
Policy Gradient Algorithms
DRL & Meta-Learning Series
Understanding AC Methods
Distributional RL
TD error vs advantage vs Bellman error

Adversial Learning and Imitation Learning

Opportunities

ML is such a promising field that contains a lot of opportunities for students:

Miscellaneous

AI Conference Due
Tips for Research, a fantastic blog