snowdj / CS228_PGM
🌀 Stanford CS 228 - Probabilistic Graphical Models
☆84Updated 6 years ago
Alternatives and similar repositories for CS228_PGM:
Users that are interested in CS228_PGM are comparing it to the libraries listed below
- Material for the "Probabilistic Machine Learning" Course at the University of Tübingen, Summer Term 2023☆152Updated last year
- 🌲 Stanford CS 228 - Probabilistic Graphical Models☆129Updated 8 months ago
- Probabilistic Deep Learning finds its application in autonomous vehicles and medical diagnoses. This is an increasingly important area of…☆65Updated 5 months ago
- Notebooks for "Probabilistic Machine Learning" book☆202Updated 3 years ago
- This is a companion to the ‘Mathematical Foundations’ section of the book, Mathematics for Machine Learning by Marc Deisenroth, Aldo Fais…☆270Updated 4 years ago
- 🌀 Stanford CS 228 - Probabilistic Graphical Models☆122Updated 6 years ago
- ☆149Updated 3 years ago
- ☆78Updated 2 years ago
- DS-GA 1013 Mathematical Tools for Data Science☆52Updated 4 years ago
- Repository for the course Probabilistic Machine Learning at Tübingen University☆23Updated 4 years ago
- Solutions for David Barber's "Bayesian Reasoning and Machine Learning" Book☆19Updated 3 years ago
- legend☆200Updated last year
- Notes for the Numerics of Machine Learning Lecture Course at the University of Tübingen☆202Updated last year
- Materials of the Nordic Probabilistic AI School 2022.☆177Updated 2 years ago
- Jupyter notebooks with the Python equivalent to the R code sections in Blitzstein and Hwang's Introduction To Probability, Second Edition☆73Updated 6 years ago
- Bayesian Statistics MOOC by Coursera - Solutions in Python☆31Updated last year
- CS 7301: Spring 2021 Course on Advanced Topics in Optimization in Machine Learning☆176Updated 4 years ago
- Computer Vision and Pattern Recognition, NUS CS4243, 2022☆169Updated 3 years ago
- Materials of the Nordic Probabilistic AI School 2023.☆91Updated last year
- ☆29Updated 3 years ago
- Python skeleton code for assignments of Probabilistic Graphical Models course on Coursera.☆8Updated 3 years ago
- Here are the notebooks for the Gaussian Processes and Bayesian Optimization course. The notebooks can be executed in Google Colab.☆27Updated 10 months ago
- Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, ca…☆170Updated 11 months ago
- List of Computer Science courses with video lectures.☆25Updated 3 years ago
- Repository for ML in Practice Course at CMU (10-718)☆62Updated last year
- Repository with all material for SMILES, the Summer School of Machine Learning at Skoltech, taking place from the 16th to the 21st of Aug…☆55Updated 4 years ago
- Introduction to Gaussian Processes☆29Updated 6 years ago
- ☆49Updated last year
- Unofficial implementation in Python porting of the book "Algorithms for Optimization" (2019) MIT Press by By Mykel J. Kochenderfer and Ti…☆46Updated 2 years ago
- Code for the book "Mathematical Introduction to Deep Learning: Methods, Implementations, and Theory"☆141Updated last year