1256 Open source projects that are alternatives of or similar to Statistical Learning

PHP-ML - Machine Learning library for PHP

Collection of stats, modeling, and data science tools in Python and R.

🍊 📊 💡 Orange: Interactive data analysis

потоковый курс "Машинное обучение и анализ данных (Machine Learning and Data Mining)" на факультете ВМК МГУ имени М.В. Ломоносова

Materials for GWU DNSC 6279 and DNSC 6290.

Google Cloud Dataflow provides a simple, powerful model for building both batch and streaming parallel data processing pipelines.

TSrepr: R package for time series representations

Measure and visualize machine learning model performance without the usual boilerplate.

R package to interface with OpenML

📝 Подборка ресурсов по машинному обучению

A Python 3 library making time series data mining tasks, utilizing matrix profile algorithms, accessible to everyone.

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A curated list of data mining papers about fraud detection.

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Multi-class confusion matrix library in Python

Python Data Science and Machine Learning Library for the Ethereum and ERC-20 Blockchain

Dex : The Data Explorer -- A data visualization tool written in Java/Groovy/JavaFX capable of powerful ETL and publishing web visualizations.

A Julia machine learning framework

The Accelerator is a tool for fast and reproducible processing of large amounts of data.

IPython widgets, interactive plots, interactive machine learning

Machine learning fundamentals lesson in interactive notebooks

Apuntes personales sobre estadística, machine learning y lenguaje de programación R

Scraping statistics, predicting NBA player performance with neural networks and boosting algorithms, and optimising lineups for Draft Kings with genetic algorithm. Capstone Project for Machine Learning Engineer Nanodegree by Udacity.

Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

Simple API for UCI Machine Learning Dataset Repository (search, download, analyze)

NFStream: a Flexible Network Data Analysis Framework.

ELKI Data Mining Toolkit

pyclustring is a Python, C++ data mining library.

Statistical Machine Intelligence & Learning Engine

model-describer : Making machine learning interpretable to humans

Introduction to Data Science

CleverCSV is a Python package for handling messy CSV files. It provides a drop-in replacement for the builtin CSV module with improved dialect detection, and comes with a handy command line application for working with CSV files.

Automated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost

👨🏽‍🏫You can learn about what data science is and why it's important in today's modern world. Are you interested in data science?🔋

LAMA - automatic model creation framework

An implementation of "Network Representation Learning with Rich Text Information" (IJCAI '15).

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Succinct Machine Learning algorithm implementations from scratch in Python, solving real-world problems (Notebooks and Book). Examples of Logistic Regression, Linear Regression, Decision Trees, K-means clustering, Sentiment Analysis, Recommender Systems, Neural Networks and Reinforcement Learning.

eBay's TSV Utilities: Command line tools for large, tabular data files. Filtering, statistics, sampling, joins and more.

MLBox is a powerful Automated Machine Learning python library.

A high-level machine learning and deep learning library for the PHP language.

Practical Data Science with Ruby based tools.

Python class to scrape data from rightmove.co.uk and return listings in a pandas DataFrame object

Machine Learning in R

Ensemble learning related books, papers, videos, and toolboxes

Artificial Neural Networks for Scala

The "Python Machine Learning (1st edition)" book code repository and info resource

An efficient Python implementation of the Apriori algorithm.

A Portfolio of my Data Science Projects

Explore high-dimensional datasets and how your algo handles specific regions.

Курс "Прикладные задачи анализа данных" (ВМК, МГУ имени М.В. Ломоносова)

A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4,5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting (GBDT, GBRT, GBM), Random Forest and Adaboost w/categorical features support for Python

Topic Modelling for Humans

Complete machine learning model codes

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

Code of the IPython Cookbook, Second Edition, by Cyrille Rossant, Packt Publishing 2018 [read-only repository]

Highly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

A curated list of awesome machine learning interpretability resources.