LovelyBuggies/Awesome_ML

Some good resources to study machine learning 📖

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
  • Mathematics Basics
  • Physics Basics
  • Tensor Theory
  • Machine Learning Basics
  • Computer Vision
  • Natural Language Processing
  • Distributed Deep Learning
  • Control Theory and Reinforcement Learning
  • Adversial Learning and Imitation Learning
  • Opportunities
  • Miscellaneous

Generated with markdown-toc

Mathematics Basics

• fast.ai: numerical-linear-algebra
• Einstein Summation in Deep Learning

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:

• UCB: ML@Berkley
• 林轩田机器学习基础(bilibili)
• Columbia: CS4771 Machine Learning
• Cheat sheet for Data Scientists

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

• GAN VS Actor-Critic
• KD 20篇 paper 回顾
• KD: A Survey
• KD and S-T Learning for CV: A Review

Opportunities

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

• BAIR
• OpenAI Jobs
• DeepMind Research Jobs
• Top AI Fellowship
• Fellowship & Award Opportunities
• Open Source Projects
• Apple Career for ML
• AIRS Research
• IDEA Research
• MSRA Jobs
• Google Research
• Facebook AI
• ByteDance AI Lab
• Tencent AI Lab
• Amazon Science
• Insight Research Centre

Miscellaneous

• AI Conference Due
• Tips for Research, a fantastic blog