fennJam

fennJam's Stars

• UnravelSports/unravelsports

  The unravelsports package aims to aid researchers, analysts and enthusiasts by providing intermediary steps in the complex process of turning raw sports data into meaningful information and actionable insights.

  Language:Python17

• roboflow/sports

  computer vision and sports

  Language:Python2k198

• hhughes-dot/Scaling-Tracking-Across-the-World-Game

  Language:Jupyter Notebook41

• rasbt/LLMs-from-scratch

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

  Language:Jupyter Notebook25.2k2.7k

• firmai/financial-machine-learning

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

  Language:Python6.8k1.2k

• ossu/computer-science

  🎓 Path to a free self-taught education in Computer Science!

  168k21.2k

• JeffSackmann/tennis_slam_pointbypoint

  Point-by-point data for Grand Slams, 2011-current

  16577

• wesm/pydata-book

  Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

  Language:Jupyter Notebook21.9k15.1k

• academic/awesome-datascience

  :memo: An awesome Data Science repository to learn and apply for real world problems.

  24.5k5.8k

• Developer-Y/cs-video-courses

  List of Computer Science courses with video lectures.

  66.3k9k

• alexeygrigorev/data-science-interviews

  Data science interview questions and answers

  Language:HTML8.7k1.9k

• visenger/awesome-mlops

  A curated list of references for MLOps

  12.4k1.9k

• mberk/betfairviz

  Create visualisations of Betfair order books

  Language:Python3211

• betcode-org/betfair

  betfairlightweight - Betfair API-NG python wrapper (with streaming)

  Language:Python425147

• facebookresearch/dino

  PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO

  Language:Python6.2k898

• andkret/Cookbook

  The Data Engineering Cookbook

  13.5k2.5k

• Avik-Jain/100-Days-Of-ML-Code

  100 Days of ML Coding

  44.4k10.4k

• MAIF/shapash

  🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

  Language:Jupyter Notebook2.7k330

• BETDAQ/AAPI

  Language:Java41

• josephmisiti/awesome-machine-learning

  A curated list of awesome Machine Learning frameworks, libraries and software.

  Language:Python64.9k14.6k

• trekhleb/javascript-algorithms

  📝 Algorithms and data structures implemented in JavaScript with explanations and links to further readings

  Language:JavaScript186k30k

• getify/You-Dont-Know-JS

  A book series on JavaScript. @YDKJS on twitter.

  179k33.4k

• lydiahallie/javascript-questions

  A long list of (advanced) JavaScript questions, and their explanations :sparkles:

  62k8.8k

• elsewhencode/project-guidelines

  A set of best practices for JavaScript projects

  Language:JavaScript29.4k3.2k

• ryanmcdermott/clean-code-javascript

  :bathtub: Clean Code concepts adapted for JavaScript

  Language:JavaScript91.1k12.2k

• leonardomso/33-js-concepts

  📜 33 JavaScript concepts every developer should know.

  Language:JavaScript63k8.8k

• TheAlgorithms/JavaScript

  Algorithms and Data Structures implemented in JavaScript for beginners, following best practices.

  Language:JavaScript32k5.5k

• DrkSephy/es6-cheatsheet

  ES2015 [ES6] cheatsheet containing tips, tricks, best practices and code snippets

  Language:JavaScript13.4k1.1k

• Asabeneh/30-Days-Of-JavaScript

  30 days of JavaScript programming challenge is a step-by-step guide to learn JavaScript programming language in 30 days. This challenge may take more than 100 days, please just follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw

  Language:JavaScript42.4k9.8k

• statsbomb/open-data

  Free football data from StatsBomb

  2.4k760