Stars
Slim(toolkit): Don't change anything in your container image and minify it by up to 30x (and for compiled languages even more) making it secure too! (free and open source)
The lazier way to manage everything docker
Lightning-fast and Powerful Code Editor written in Rust
A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. All in a modern, AI-native editor.
Firefly III: a personal finances manager
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
An open-source remote desktop application designed for self-hosting, as an alternative to TeamViewer.
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
A natural language interface for computers
Musicpy is a music programming language in Python designed to write music in very handy syntax through music theory and algorithms.
Hyprland is an independent, highly customizable, dynamic tiling Wayland compositor that doesn't sacrifice on its looks.
music21 is a Toolkit for Computational Musicology
Multi functional app to find duplicates, empty folders, similar images etc.
Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
🆙 Upscayl - #1 Free and Open Source AI Image Upscaler for Linux, MacOS and Windows.
Intelligently optimizes technical indicators and optionally selects the least intercorrelated for use in machine learning models
Questions to ask the company during your interview
Code for the paper Hybrid Spectrogram and Waveform Source Separation
10 Weeks, 20 Lessons, Data Science for All!
A pandoc LaTeX template to convert markdown files to PDF or LaTeX.
🧮 A collection of resources to learn mathematics for machine learning
Teaches step-by-step to analysis stock data in python.
Code repository for Deep Learning with Keras published by Packt
PacktPublishing / Machine-Learning-for-Algorithmic-Trading-Second-Edition
Forked from stefan-jansen/machine-learning-for-tradingCode and resources for Machine Learning for Algorithmic Trading, 2nd edition.
Quantitative analysis, strategies and backtests
Latex code for making neural networks diagrams
Comprehensive language-agnostic guidelines on variables naming. Home of the A/HC/LC pattern.