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Starred repositories
Data science interview questions and answers
Development Kit for the SoccerNet Challenge
An analysis and visualization R package that works with publicly available soccer data
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
Identify young outliers in football.
A list of interesting graph neural networks (GNN) links with a primary interest in recommendations and tensorflow that is continually updated and refined
Turn (almost) any Python command line program into a full GUI application with one line
Python programs, usually short, of considerable difficulty, to perfect particular skills.
A resource for learning about Machine learning & Deep Learning
Julia implementations of the book "Bayesian Methods for Hackers"
The Narya API allows you track soccer player from camera inputs, and evaluate them with an Expected Discounted Goal (EDG) Agent. This repository contains the implementation of the flowing paper htt…
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
Answers to 120 commonly asked data science interview questions.
Excerpts of code used in xPSG Sports Analytics Challenge
📊⚽ A collection of football analytics projects, data, and analysis by Edd Webster (@eddwebster), including a curated list of publicly available resources published by the football analytics community.
Maia is a human-like neural network chess engine trained on millions of human games.
This repository contains the data and code used in a manuscript "Estimating the change in soccer's home advantage during the Covid-19 pandemic using bivariate Poisson regression", by Luke Benz and …
Models and examples built with TensorFlow
Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
An interactive TLS-capable intercepting HTTP proxy for penetration testers and software developers.
Code for Kaggle Data Science Competitions
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
Google Research
A Julia package for Gaussian Processes
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more