Repository Index

100 Days of ML Coding

• machine-learning
• machine-learning-algorithms
• infographics
• tutorial

TranslatedAiLearning: Data Analysis + Machine Learning in Action + Linear Algebra + PyTorch + NLTK + TF2

• fp-growth
• apriori
• mahchine-leaning
• naivebayes

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

• bayesian-methods
• pymc
• mathematical-analysis
• jupyter-notebook

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

Machine learning, in numpy

• machine-learning
• neural-networks
• topic-modeling
• gaussian-mixture-models

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

• machine-learning
• deep-learning
• deep-neural-networks
• pattern-recognition

Translated:zap: Machine Learning in Action (Python3): kNN, decision tree, Bayes, logistic regression, SVM, linear regression, tree regression

• adaboost
• logistic
• svm
• smo

Bayesian Modeling and Probabilistic Programming in Python

• python
• statistical-analysis
• bayesian-inference
• mcmc

Deep universal probabilistic programming with Python and PyTorch

• python
• pytorch
• machine-learning
• bayesian

A Python implementation of global optimization with gaussian processes.

• optimization
• gaussian-processes
• bayesian-optimization
• python

Automated Machine Learning with scikit-learn

• automl
• scikit-learn
• automated-machine-learning
• hyperparameter-optimization

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

• h2o
• machine-learning
• data-science
• deep-learning

Bayesian optimization in PyTorch

Python Toolkit for Causal and Probabilistic Reasoning

• python
• bayesian-networks
• causal-inference
• causal-discovery

Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies

• machine-learning
• scikit-learn
• statistical-learning
• xgboost

A modular active learning framework for Python

• scikit-learn
• machine-learning
• python
• active-learning

Enhancing {ggplot2} plots with statistical analysis 📊📣

• ggplot-extension
• dataviz
• r
• statistical-analysis

Drawing Bayesian networks, graphical models, tensors, technical frameworks, and illustrations in LaTeX.

• latex
• machine-learning

Exploratory analysis of Bayesian models with Python

• python
• bayesian
• closember

Deep probabilistic analysis of single-cell and spatial omics data

• scrna-seq
• variational-bayes
• variational-autoencoder
• cite-seq

Spearmint Bayesian optimization codebase

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

• bayesian-optimization
• bayesian-optimisation
• hyperparameter-optimization
• hyperparameter-tuning

A Bayesian database table for querying the probable implications of data as easily as SQL databases query the data itself. New implementation in http://github.com/probcomp/bayeslite

Naive Bayesian Classification for Golang.