Machine Learning

This repository collects guidance and examples for building retrieval-augmented generation applications.

This repository curates academic papers and related resources about federated learning systems.

This repository teaches 22 prompt engineering techniques through Jupyter Notebook tutorials.

Use Learnergy, a Python library for training and working with energy-based machine learning models.

Discover more than 800 free public APIs in this community list for programmers.

Python developers can use Zipline’s event-driven library to backtest algorithmic trading strategies.

This repository explains popular machine learning algorithms with MATLAB and Octave code examples and mathematics.

Agentic Context Engine aims to help agents learn from their execution experience.

Data Science at Home is a technology podcast hosted by Francesco Gadaleta.

Notebooks and code for the book "Introduction to Machine Learning with Python".

dr-doc-search lets users converse with a book in PDF form using GPT-3.

A daily study plan for people working toward becoming machine learning engineers.

Awesome YouTubers collects channels that teach a range of subjects through video.

Karate Club offers algorithms for unsupervised learning on graph data in Python.

A curated list of Monte Carlo tree search papers with implementations.

System Designer teaches software architecture through lessons, quizzes, and case studies.

Unsupervised machine learning with multivariate Gaussian mixture model.

Live countdowns for global AI conferences & exhibitions in Machine Learning, Computer Vision, Robotics & NLP.

Browse large JSONL, Parquet, and CSV datasets in VS Code with the Bread Dataset Viewer extension.

This tutorial walks through training and deploying a machine learning REST API that predicts cryptocurrency prices in ten steps.

This LLM course combines learning roadmaps with Google Colab notebooks for studying large language models.

Matthew Russell’s site discusses Mining the Social Web and data-driven analysis.

This repository collects gradient boosting research papers with implementations.

Feature Engine provides Python tools for feature engineering and selection that are compatible with scikit-learn.