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

Python toolkit for quantitative finance

A curated list of resources dedicated to Deep Hedging

Analysis on systematic trading strategies (e.g., trend-following, carry and mean-reversion). The result is regularly updated.

This project is dedicated to the implementation and research of Kolmogorov-Arnold convolutional networks. The repository includes implementations of 1D, 2D, and 3D convolutions with different kern…

Self-study on Larry Wasserman's "All of Statistics"

An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch.

Understanding Kolmogorov-Arnold Networks: A Tutorial Series on KAN using Toy Examples

Graphic notes on Gilbert Strang's "Linear Algebra for Everyone"

A complete daily plan for studying to become a machine learning engineer.

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

A unified framework for tabular probabilistic regression and probability distributions in python

A curated list of practical financial machine learning tools and applications.

Friends don't let friends make certain types of data visualization - What are they and why are they bad.

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas

📚 Freely available programming books

Machine Learning in Finance: From Theory to Practice Book

A modified CNN architecture using Kolmogorov-Arnold Networks

A comprehensive collection of KAN(Kolmogorov-Arnold Network)-related resources, including libraries, projects, tutorials, papers, and more, for researchers and developers in the Kolmogorov-Arnold N…

Practical Guide to Applied Conformal Prediction, published by Packt

Omnigrok: Grokking Beyond Algorithmic Data

Kolmogorov Arnold Networks

Code for the AISTATS 2024 Paper "From Data Imputation to Data Cleaning - Automated Cleaning of Tabular Data Improves Downstream Predictive Performance"

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

The best repository showing why transformers might not be the answer for time series forecasting and showcasing the best SOTA non transformer models.

A curated list of awesome libraries, packages, strategies, books, blogs, tutorials for systematic trading.

Zipline, a Pythonic Algorithmic Trading Library

ArcticDB is a high performance, serverless DataFrame database built for the Python Data Science ecosystem.