Stars
An educational resource to help anyone learn deep reinforcement learning.
Transparent and Efficient Financial Analysis
Investment Research for Everyone, Everywhere.
A playbook for systematically maximizing the performance of deep learning models.
The simplest, fastest repository for training/finetuning medium-sized GPTs.
A curated list of practical financial machine learning tools and applications.
System design interview for IT companies
https://huyenchip.com/ml-interviews-book/
This is a database of 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets.
An Open-Source Package for Information Retrieval.
Model interpretability and understanding for PyTorch
🪄 Turns your machine learning code into microservices with web API, interactive GUI, and more.
FinRL: Financial Reinforcement Learning. 🔥
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Find your trading edge, using the fastest engine for backtesting, algorithmic trading, and research.
NeuralProphet: A simple forecasting package
Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas…
A complete set of volatility estimators based on Euan Sinclair's Volatility Trading
The code for "Leveraging an Efficient and Semantic Location Embedding to Seek New Ports of Bike Share Services" in IEEE BigData 2020
Beyond Accuracy: Behavioral Testing of NLP models with CheckList
Quantitative finance research tools in Python
Automatic extraction of relevant features from time series:
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
Statistical and Algorithmic Investing Strategies for Everyone
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
allRank is a framework for training learning-to-rank neural models based on PyTorch.