teoliphant / Probabilistic-Programming-and-Bayesian-Methods-for-HackersLinks
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming in data analysis with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
☆14Updated 12 years ago
Alternatives and similar repositories for Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
Users that are interested in Probabilistic-Programming-and-Bayesian-Methods-for-Hackers are comparing it to the libraries listed below
Sorting:
- Notebooks for "Python for Signal Processing" book☆11Updated 10 years ago
- Lectures for INFO8004 Advanced Machine Learning, ULiège☆115Updated 8 months ago
- Jupyter Notebooks for Computational Linear Algebra course, taught summer 2018 in USF MSDS program☆279Updated 7 years ago
- An implementation of convolutional networks in NumPy!☆82Updated 4 years ago
- Machine learning algorithms☆113Updated 6 years ago
- Contains useful deep learning notations for writing blogs, presentations, and papers.☆47Updated 5 years ago
- Thinking in tensors, writing in PyTorch (a hands-on deep learning intro)☆392Updated 11 months ago
- Repository for CS282R: Robust Machine Learning at Harvard University.☆73Updated 7 years ago
- Code examples for my Interpretable Machine Learning Blog Series☆57Updated 5 years ago
- Designing Deep neural network architectures using topologies from the world of Complex Networks/network Science☆91Updated 6 years ago
- Jupyter notebooks with the Python equivalent to the R code sections in Blitzstein and Hwang's Introduction To Probability, Second Edition☆75Updated 6 years ago
- Lecture Slides, Exercises, and Deployment Materials for "Foundations of Numerical Computing"☆81Updated 3 years ago
- DataGene - Identify How Similar TS Datasets Are to One Another (by @firmai)☆206Updated 3 years ago
- FairPut - Machine Learning Fairness Framework with LightGBM — Explainability, Robustness, Fairness (by @firmai)☆72Updated 4 years ago
- A collection of PyTorch notebooks for learning and practicing deep learning☆140Updated 5 years ago
- Python code (packaged in Docker container) to run the experiments in "A Greedy Algorithm for Quantizing Neural Networks" by Eric Lybrand …☆20Updated 4 years ago
- Ever wondered how to code your Neural Network using NumPy, with no frameworks involved?☆264Updated 6 years ago
- Implementation of various Reinforcement Learning Algorithms☆27Updated 7 years ago
- A flexible neural network framework for running experiments and trying ideas.☆82Updated 5 years ago
- Simple Experiments to Give Some Intuition behind Deep Neural Networks☆38Updated 7 years ago
- ☆22Updated 5 years ago
- kaggle☆29Updated 7 years ago
- A tiny lib with pocket-sized implementations of machine learning models in NumPy, most of which will fit in a tweet.☆569Updated 2 years ago
- Notes on mathematical topics that pertain to machine learning☆112Updated 4 years ago
- Specification files for the Foundations of Applied Mathematics lab curriculum. https://foundations-of-applied-mathematics.github.io/☆55Updated last year
- Curated lists of fastai resources: blog posts, twitter threads etc.☆146Updated 5 years ago
- Pytorch Cheatsheet☆91Updated 7 years ago
- a python based module (bot) to generate kaggle baseline kernels☆26Updated 7 years ago
- The code repository for examples in the O'Reilly book 'Generative Deep Learning' using Pytorch☆184Updated 6 years ago
- Collection of resources for self-studying mathematics and machine learning.☆54Updated 4 years ago