12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.

100 Days of ML Coding

Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.

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.

A complete daily plan for studying to become a machine learning engineer.

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

Collection of various algorithms in mathematics, machine learning, computer science, physics, etc implemented in C for educational purposes.

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

Code for Machine Learning for Algorithmic Trading, 2nd edition.

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域

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

手写实现李航《统计学习方法》书中全部算法

Minimal and clean examples of machine learning algorithms implementations

A resource for learning about Machine learning & Deep Learning

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

:speech_balloon: Machine Learning Course with Python:

Matlab code of machine learning algorithms in book PRML

Uplift modeling and causal inference with machine learning algorithms

cuML - RAPIDS Machine Learning Library

This repository is a compilation of free resources for learning Data Science.

A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

Python code for common Machine Learning Algorithms

Plain python implementations of basic machine learning algorithms

A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks

Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.

Quant/Algorithm trading resources with an emphasis on Machine Learning

Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web