Popular GitHub Repositories for Educational Linear Regression Example

100 Days of ML Coding

AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2

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.

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

RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.

MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville

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

Example ? Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using ? Amazon SageMaker.

Turn your two-bit doodles into fine artworks with deep neural networks, generate seamless textures from photos, transfer style from one image to another, perform example-based upscaling, but wait... there's more! (An implementation of Semantic Style Transfer.)

An open-source, low-code machine learning library in Python

A unified framework for machine learning with time series

WebGL-accelerated ML // linear algebra // automatic differentiation for JavaScript.

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

CUDA Templates for Linear Algebra Subroutines

Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.

A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

Postgres with GPUs for ML/AI apps.

An adversarial example library for constructing attacks, building defenses, and benchmarking both