Links
Research
- De-Mystifying Good Research and Good Papers
- You and Your Research
- How to Pick a Graduate Advisor
- The Ph.D. Grind
Machine learning basics
- AI Conference deadlines
- Machine Learning: a Probabilistic Perspective
- Pattern Recognition and Machine Learning
- Understanding Machine Learning: From Theory to Algorithms
- Bayesian Data Analysis
- Deep Learning
- Reinforcement Learning: An Introduction
- Key Papers in Deep RL
- Gaussian Process for Machine Learning
- All of Statistics
- Foundations of Machine Learning
- Partially Observed Markov Decision Processes
- The Matrix Cookbook
- Mike Jordan’s Reading List
- Notes on Deep Learning for NLP
- Colah’s Blog
- Montreal AI 101
- McGill RLLAB courses
- MILA courses
- MILA events
Software
- Unofficial Windows Binaries for Python Extension Packages
- Linux screen
- Lightspeed matlab toolbox
- igraph
- Anaconda
- julia
Online courses
- Probabilistic Graphical Models
- Probabilistic Graphical Models
- Princeton
- Introduction to Deep Learning
- NLP with Deep Learning
- MLSS
- DLSS
- Deep Learning
- Full Stack Deep Learning Bootcamp
- fast.ai
- cs231n.stanford.edu
- Machine Learning for Time Series
- Deep RL Bootcamp
- cs294@berkeley
- Advanced Deep Learning & Reinforcement Learning
Research groups
- Probabilistic Machine Learning Group
- Uber Visualization
- Yan Liu
- Rose Yu
- Tatsuya Yokota
- Jessie Li
- Zhanxing Zhu
- Cyrus Shahabi
- Alexandre Bayen
- Marc Barthelemy
- Animashree Anandkumar
- Xingjian Shi
- Tom Minka
- Daniel Gatica-Perez
- Marta Gonzalez
- Barabasi Lab
- Yu Zheng
- Jingyuan Wang
- Qibin Zhao
- Jing Gao
- Mingyuan Zhou
- Daniele Quercia
Writing & Latex
- How to write a great research paper (video)
- How to write a great research paper (slide)
- Mathematical Writing (Knuth)
- Writing ariticles for scientific journals
- Improving your scientific writing: a short guide
- overleaf
- linggle
- netspeak
- thesaurus
- ITLS Transportation journal ranking
- The Elements of Style
- excel2latex