Showing 1-20 of 99 projects
100-day ML coding challenge with implementations and tutorials
AI learning repository with tutorials and implementations for machine learning, deep learning, and data analysis
Barebones NumPy ML implementations for learning
A comprehensive code repository and resource for learning machine learning with Python.
Statsmodels is a Python library for statistical modeling and econometrics, providing tools for data analysis and prediction.
Open-source machine learning library in Python with implementations of popular algorithms like kNN, decision trees, and SVM.
Miller is a powerful CLI tool for processing tabular data like CSV, TSV, and JSON, similar to awk, sed, and other Unix utilities.
An open-source, low-code machine learning library in Python for building and training machine learning models.
A unified framework for machine learning with time series in Python, focused on forecasting, anomaly detection, and more.
A high-performance gradient boosting library for machine learning tasks on CPUs and GPUs.
An ultra-simple, state-of-the-art codebase for autoregressive image generation using advanced AI models.
A comprehensive PyTorch tutorial for building neural networks and AI models with ease
Automatically captures and compares CSS styles across different browser versions for developers.
Solutions and notes for the Machine Learning Specialization by Andrew NG on Coursera.
Automate running Lighthouse performance audits and track web performance improvements across commits.
Postgres-based database with GPU acceleration for machine learning and AI applications.
A collection of notebooks covering quantitative finance and numerical methods in Python.
Smile is a comprehensive statistical machine learning and data science library for Java developers.
A state-of-the-art deep learning library for time series and sequence modeling in PyTorch/fastai.
A fast, header-only C++ machine learning library for developers building AI-powered applications.
Get weekly updates on trending AI coding tools and projects.