A collective list of free APIs

Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.

An opinionated list of awesome Python frameworks, libraries, software and resources.

All Algorithms implemented in Python

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

FastAPI framework, high performance, easy to learn, fast to code, ready for production

Deep Learning for humans

scikit-learn: machine learning in Python

Inference code for Llama models

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

TensorFlow code and pre-trained models for BERT

120+ interactive Python coding interview challenges (algorithms and data structures). Includes Anki flashcards.

The fundamental package for scientific computing with Python.

Minimal examples of data structures and algorithms in Python

Best Practices on Recommendation Systems

A Deep Learning based project for colorizing and restoring old images (and video!)

Machine learning, in numpy

🤖 Chat with your SQL database 📊. Accurate Text-to-SQL Generation via LLMs using RAG 🔄.

100 numpy exercises (with solutions)

A MNIST-like fashion product database. Benchmark 👇

This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.

Open Machine Learning Course

A collection of machine learning examples and tutorials.

A library that allows you to easily mock out tests based on AWS infrastructure.

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

Install Jenkins, configure Docker as slave, set up cicd, deploy applications to k8s using Argo CD in GitOps way.

A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

This repository is a curated collection of links to various courses and resources about Artificial Intelligence (AI)

Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.

Visual analysis and diagnostic tools to facilitate machine learning model selection.