From the Tensor to Stable Diffusion, a rough outline for a 9 week course.

The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.

You like pytorch? You like micrograd? You love tinygrad! ❤️

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

Solutions for projects.

Learn how to design, develop, deploy and iterate on production-grade ML applications.

Python Jira library. Development chat available on https://matrix.to/#/#pycontribs:matrix.org

This is a database of 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets.

Portfolio Optimization and Quantitative Strategic Asset Allocation in Python

Download market data from Yahoo! Finance's API

Search inside YouTube videos using natural language

Solidity, the Smart Contract Programming Language

Track P/L, portfolio performance, net credit after rolls, for tastytraders

PRAW, an acronym for "Python Reddit API Wrapper", is a python package that allows for simple access to Reddit's API.

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

Curated list of Python resources for data science.

Portfolio analytics for quants, written in Python

Machine Learning in Asset Management (by @firmai)

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.

A Python wrapper around the Twitter API.

Financial Markets Data Visualization using Matplotlib

An unofficial, reverse-engineered Python API for tastyworks.

A collection of learning resources for curious software engineers

RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference,…