lucasrm25 / Probabilistic-Machine-LearningLinks
Repository for the course Probabilistic Machine Learning at Tübingen University
☆26Updated 5 years ago
Alternatives and similar repositories for Probabilistic-Machine-Learning
Users that are interested in Probabilistic-Machine-Learning are comparing it to the libraries listed below
Sorting:
- Material for the "Probabilistic Machine Learning" Course at the University of Tübingen, Summer Term 2023☆175Updated last year
- 🌀 Stanford CS 228 - Probabilistic Graphical Models☆88Updated 6 years ago
- Materials of the Nordic Probabilistic AI School 2023.☆91Updated last year
- Notes for the Numerics of Machine Learning Lecture Course at the University of Tübingen☆213Updated last year
- ☆85Updated 2 years ago
- Probabilistic Deep Learning finds its application in autonomous vehicles and medical diagnoses. This is an increasingly important area of…☆69Updated 9 months ago
- ☆20Updated 2 years ago
- Materials of the Nordic Probabilistic AI School 2022.☆182Updated 2 years ago
- Here are the notebooks for the Gaussian Processes and Bayesian Optimization course. The notebooks can be executed in Google Colab.☆27Updated last year
- Bayesian Learning and Neural Networks (jupyter book sources)☆56Updated 2 years ago
- Representation Learning MSc course Summer Semester 2023☆82Updated 2 years ago
- The only guide you need to learn everything about GMM☆128Updated 8 months ago
- Notebooks for "Probabilistic Machine Learning" book☆202Updated 3 years ago
- A collection of awesome mathematics and computer science courses☆131Updated 7 months ago
- Computer Vision and Pattern Recognition, NUS CS4243, 2022☆172Updated 3 years ago
- Neat Bayesian machine learning examples☆58Updated 2 months ago
- 🌲 Stanford CS 228 - Probabilistic Graphical Models☆136Updated 11 months ago
- Exercises and supplementary material for the deep learning course 02456 using PyTorch.☆330Updated 10 months ago
- Course material for 1RT700 Statistical Machine Learning☆62Updated 6 months ago
- This is a companion to the ‘Mathematical Foundations’ section of the book, Mathematics for Machine Learning by Marc Deisenroth, Aldo Fais…☆284Updated 4 years ago
- ☆51Updated last year
- Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, ca…☆174Updated last year
- Interactive textbook on state-space models☆197Updated last year
- Python & Matlab code for the figures from the book "Learning Theory from First Principles" by Francis Bach☆123Updated last year
- 🌀 Stanford CS 228 - Probabilistic Graphical Models☆122Updated 6 years ago
- Berkeley CS182/282A Designing, Visualizing and Understanding Deep Neural Networks☆85Updated 2 years ago
- Hands-On Optimization with Python☆221Updated 4 months ago
- Introduction to Gaussian Processes☆29Updated 7 years ago
- A course on Linear Algebra using Python in Jupyter notebooks☆38Updated 2 years ago
- ☆34Updated 2 months ago