thejakeyboy / umich-eecs545-lecturesLinks
This repository contains the lecture materials for EECS 545, a graduate course in Machine Learning, at the University of Michigan, Ann Arbor.
☆220Updated 8 years ago
Alternatives and similar repositories for umich-eecs545-lectures
Users that are interested in umich-eecs545-lectures are comparing it to the libraries listed below
Sorting:
- ☆77Updated 8 years ago
- Materials for EECS 445, an undergraduate Machine Learning course taught at the University of Michigan, Ann Arbor.☆98Updated 8 years ago
- ☆31Updated 7 years ago
- ☆83Updated 8 years ago
- DS-GA-1011 Natural Language Processing with Representation Learning☆81Updated 7 years ago
- Personal and biased selection of ML resources☆150Updated 5 years ago
- Python Version of BRML toolbox for Bayesian Reasoning and Machine Learning☆163Updated 9 years ago
- DS-GA-1005 Inference and Representation☆15Updated 7 years ago
- STA663 Statistical Computing and Computation, Spring 2016☆87Updated 9 years ago
- UCL MSc Computational Statistics and Machine Learning Revision Notes☆286Updated 6 years ago
- Courera Version of Graphical Model.. Cooperate with Jian Guo.☆122Updated 8 years ago
- Materials for Bayesian Methods in Machine Learning Course☆88Updated 6 months ago
- Code for Implementation, Inference, and Learning of Bayesian and Markov Networks along with some practical examples.☆104Updated 12 years ago
- Inference and Representation (DS-GA-1005, CSCI-GA.2569), fall 18☆66Updated 6 years ago
- Deep exponential families (DEFs)☆55Updated 7 years ago
- Course materials for STA663☆37Updated 9 years ago
- Compilation of resources found around the web connected with Machine Learning, Deep Learning & Data Science in general.☆92Updated 7 years ago
- Contains LaTeX, SciPy and R code providing solutions to exercises in Elements of Statistical Learning (Hastie, Tibshirani & Friedman)☆290Updated 11 years ago
- Material for the Montréal Deep Learning Summer School 2017☆77Updated 7 years ago
- Bayesian Machine Learning☆207Updated 2 years ago
- EE227C (Spring 2018) Course page☆224Updated 4 years ago
- Repository of my thesis "Understanding Random Forests"☆525Updated 8 years ago
- Solutions to exercises from Machine Learning: A Probabilistic Perspective by Kevin P. Murphy☆47Updated 8 years ago
- Slides and exercises for the Theano tutorial at the Deep Learning School in Stanford, September 24-25, 2016☆114Updated 8 years ago
- A collection of tutorials on neural networks, using Theano☆222Updated 2 years ago
- The pdf and LaTeX for each paper (and sometimes the code and data used to generate the figures).☆72Updated 8 years ago
- Torch notebooks and slides for the Bay Area Deep Learning Summer School☆97Updated 8 years ago
- Experiments in Bayesian Machine Learning☆69Updated 5 years ago
- ☆38Updated 6 years ago
- Right whale recognition☆55Updated 9 years ago