cliburn / sta-663-2018Links
☆73Updated 6 years ago
Alternatives and similar repositories for sta-663-2018
Users that are interested in sta-663-2018 are comparing it to the libraries listed below
Sorting:
- Course notes for Computational Statistics and Statistical Compuing☆63Updated 6 years ago
- Jupyter notebooks and other materials developed for the Columbia course APMA 4300☆286Updated 2 years ago
- Resources for STA 633 class☆169Updated 8 years ago
- Materials for "Bayesian Methods for Machine Learning" Coursera MOOC☆135Updated 5 years ago
- ☆232Updated 3 years ago
- Notebooks, worksheets and homework for STA 663 class☆43Updated 8 years ago
- Tutorial on "Modern Optimization Methods in Python"☆249Updated 6 months ago
- ☆145Updated 4 years ago
- ☆38Updated 4 years ago
- ☆45Updated 5 years ago
- Bayesian Analysis with Python by Packt☆218Updated 2 years ago
- PyData London 2019 Tutorial on Markov chain Monte Carlo with PyMC3☆160Updated 5 years ago
- Presented at Scipy Conference 2019☆127Updated 5 years ago
- Material for the SciPy 2017 Cython tutorial☆143Updated 8 years ago
- CME211 Notes☆257Updated 2 years ago
- ☆174Updated 10 months ago
- Code for a tutorial on Bayesian Statistics by Allen Downey.☆356Updated 4 years ago
- my blog☆268Updated 3 years ago
- Code and data for the second edition of the textbook `Machine Learning: An Algorithm Perspective" by Stephen Marsland.☆148Updated 4 years ago
- The compiled, clean (not run) Jupyter notebooks for Elegant SciPy☆112Updated 5 years ago
- Numba tutorial materials for Scipy 2016☆144Updated 8 years ago
- ☆240Updated 7 years ago
- Specification files for the Foundations of Applied Mathematics lab curriculum. https://foundations-of-applied-mathematics.github.io/☆54Updated last year
- Lectures for INFO8004 Advanced Machine Learning, ULiège☆113Updated 5 months ago
- Lecture Slides, Exercises, and Deployment Materials for "Foundations of Numerical Computing"☆81Updated 2 years ago
- Doing Bayesian statistics in Python!☆67Updated 7 years ago
- ☆73Updated 7 years ago
- Jupyter notebooks with the Python equivalent to the R code sections in Blitzstein and Hwang's Introduction To Probability, Second Edition☆74Updated 6 years ago
- Statistical Rethinking (2nd Ed) with Tensorflow Probability☆272Updated 3 years ago
- Using computational thinking to get deep insights on the foundations of linear algebra☆115Updated 4 months ago