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aiml

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

benchm-ml

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

cookbook-code

Recipes of the IPython Cookbook, the definitive guide to high-performance scientific computing and data science in Python

coursera_msprob

coursera_py4e

coursera_pystats

datacleaner

A Python tool that automatically cleans data sets and readies them for analysis.

dive-into-machine-learning

Dive into Machine Learning with Python Jupyter notebook and scikit-learn

dunderdata

feature_engine

Feature engineering package with sklearn like functionality

featuretools

An open source python library for automated feature engineering

geostatsmodels

This is a collection of geostatistical scripts written in Python, and updated to support Python 3+.

go

Algorithms Implemented in GoLang

go-algorithms

Algorithms and data structures for golang

golearn

Machine Learning for Go

goml

On-line Machine Learning in Go (and so much more)

gonum

Gonum is a set of numeric libraries for the Go programming language. It contains libraries for matrices, statistics, optimization, and more

gorgonia

Gorgonia is a library that helps facilitate machine learning in Go.

gota

Gota: DataFrames and data wrangling in Go (Golang)

grumpy

Grumpy is a Python to Go source code transcompiler and runtime.

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

homemade-machine-learning

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

intro2stats

Introduction to Statistics using Python

kalman-and-bayesian-filters-in-python

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.

keras-tutorial

3-hour tutorial on building deep learning models with Keras.

machine-learning-books

machine-learning-with-go

Machine Learning With Go, published by Packt

ml-from-scratch

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

neural-network