physhik / Study-of-David-Mackay-s-book-Links
David Mackay's book review and problem solvings and own python codes, mathematica files
☆57Updated 7 years ago
Alternatives and similar repositories for Study-of-David-Mackay-s-book-
Users that are interested in Study-of-David-Mackay-s-book- are comparing it to the libraries listed below
Sorting:
- Materials for "Bayesian Methods for Machine Learning" Coursera MOOC☆135Updated 4 years ago
- http://cranmer.github.io/stats-ds-book☆70Updated 4 years ago
- ☆73Updated 6 years ago
- STATS305C: Applied Statistics III (Spring, 2023)☆26Updated 2 years ago
- Course notes for Computational Statistics and Statistical Compuing☆63Updated 6 years ago
- Probabilistic Deep Learning finds its application in autonomous vehicles and medical diagnoses. This is an increasingly important area of…☆65Updated 7 months ago
- Lectures for INFO8004 Advanced Machine Learning, ULiège☆113Updated 3 months ago
- Materials of the Nordic Probabilistic AI School 2019.☆130Updated 5 years ago
- Code and data for the second edition of the textbook `Machine Learning: An Algorithm Perspective" by Stephen Marsland.☆149Updated 4 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
- Some small scale experiments for my blog posts 📝☆79Updated 3 years ago
- Experiments in Bayesian Machine Learning☆69Updated 5 years ago
- Source code for 'Dynamical Systems with Applications Using Python' by Stephen Lynch☆154Updated 7 years ago
- Materials for class on topics in deep learning (STAT 991, UPenn/Wharton)☆95Updated 2 years ago
- Gaussian Process and Uncertainty Quantification Summer School 2017☆26Updated 2 years ago
- Statistical Rethinking (2nd Ed) with Tensorflow Probability☆272Updated 3 years ago
- Statistical Rethinking: A Bayesian Course Using Python and NumPyro☆90Updated 4 years ago
- Specification files for the Foundations of Applied Mathematics lab curriculum. https://foundations-of-applied-mathematics.github.io/☆53Updated 9 months ago
- ☆59Updated 6 years ago
- Example codes for the book Applied Stochastic Differential Equations☆194Updated 3 years ago
- Mathematics of Deep Learning, Courant Insititute, Spring 19☆277Updated 6 years ago
- Presented at Scipy Conference 2019☆127Updated 5 years ago
- legend☆204Updated last year
- Understanding ML and deep learning through geometry☆157Updated 3 years ago
- Learning some numerical linear algebra.☆70Updated 4 years ago
- Just a little MCMC☆227Updated last year
- More PRML Errata☆80Updated 2 years ago
- Essay on Hamiltonian Monte Carlo in PyMC3☆14Updated 2 years ago
- ☆38Updated 4 years ago
- Understanding nuts and bolts of neural networks with PyTorch☆33Updated 4 years ago