gastyr

gastyr's Stars

• f-utils/f-core

  Functional-based utils for Python following a constructivist approach.

  Language:Python33

• f-utils/f

  A python lib to ensure type safety through a functional approach.

  Language:Python2

• HomelessPhD/Wealth_in_Poetry

  "Securing Wealth in Poetry" crypto puzzle (0.03 BTC)

  Language:Python101

• soroswap/zephyr-programs

  Zephyr scripts to index Soroswap.Finance AMM (Pairs, Factory, Router) Smart Contracts

  Language:TypeScript310

• rust-lang/rustlings

  :crab: Small exercises to get you used to reading and writing Rust code!

  Language:Rust55.5k10.3k

• pcottle/learnGitBranching

  An interactive git visualization and tutorial. Aspiring students of git can use this app to educate and challenge themselves towards mastery of git!

  Language:JavaScript30.9k5.8k

• Ackee-Blockchain/school-of-solana

  School of Solana

  Language:TypeScript19477

• mfrdixon/ML_Finance_Codes

  Machine Learning in Finance: From Theory to Practice Book

  Language:Jupyter Notebook1.9k510

• kgretzky/evilginx2

  Standalone man-in-the-middle attack framework used for phishing login credentials along with session cookies, allowing for the bypass of 2-factor authentication

  Language:Go11.4k2k

• matheusfacure/python-causality-handbook

  Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.

  Language:Jupyter Notebook2.8k492

• saeed349/Advances-in-Financial-Machine-Learning

  Using Dask, a Python framework, I handle 900 million rows of S&P E-mini futures trade tick data directly on a local machine. Through exploratory data analysis, continuous series creation, and bar sampling, inspired by Marcos Lopez de Prado's work, I demonstrate efficient alternatives to costly data processing methods.

  Language:Jupyter Notebook377

• xandequant/xandequant

  Config files for my GitHub profile.

  Language:Jupyter Notebook2

• saulocatharino/Monkey

  Monkey (LMM): Image Resolution and Text Label Are Important Things for Large Multi-modal Models （CVPR 2024)

  103

• roboflow/supervision

  We write your reusable computer vision tools. 💜

  Language:Python24.6k1.8k

• amidaware/tacticalrmm

  A remote monitoring & management tool, built with Django, Vue and Go.

  Language:Python3.3k454

• deepchecks/deepchecks

  Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

  Language:Python3.7k257

• ysraell/datavis

  Material for data visualization course.

  Language:Jupyter Notebook53

• ramoonmedeiro/NBA-mvp-prev

  Modelo de Machine Learning para previsão do MVP da NBA

  Language:Python4

• youssefHosni/Data-Science-Interview-Questions-Answers

  Curated list of data science interview questions and answers

  3.7k863

• MicrosoftDocs/ml-basics

  Exercise notebooks for Machine Learning modules on Microsoft Learn

  Language:Jupyter Notebook1.8k2.3k

• khangich/machine-learning-interview

  Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.

  10.1k1.6k

• alirezadir/Machine-Learning-Interviews

  This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

  Language:Jupyter Notebook5.2k906

• pibieta/ML-course

  A set of python notebooks concerning Machine Learning, for educative purposes.

  Language:Jupyter Notebook2

• firmai/industry-machine-learning

  A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)

  Language:Jupyter Notebook7.3k1.2k

• youssefHosni/Practical-Machine-Learning-Tips

  Language:Jupyter Notebook537

• linebender/druid

  A data-first Rust-native UI design toolkit.

  Language:Rust9.6k566

• TeoMeWhy/teomerefs

  Guia de referências técnicas para carreira em dados

  1.1k109

• fschutt/azul

  Desktop GUI Framework

  Language:Rust5.9k220

• microsoft/Data-Science-For-Beginners

  10 Weeks, 20 Lessons, Data Science for All!

  Language:Jupyter Notebook28.5k5.9k

• microsoft/ML-For-Beginners

  12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

  Language:HTML70.3k14.8k