Mirza Hasanbasic's starred repositories
computer-science
:mortar_board: Path to a free self-taught education in Computer Science!
OpenBBTerminal
Investment Research for Everyone, Everywhere.
CopilotKit
A framework for building custom AI Copilots 🤖 in-app AI chatbots, in-app AI Agents, & AI-powered Textareas.
machine-learning-cheat-sheet
Classical equations and diagrams in machine learning
PyPortfolioOpt
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
Binance-volatility-trading-bot
This is a fully functioning Binance trading bot that measures the volatility of every coin on Binance and places trades with the highest gaining coins If you like this project consider donating though the Brave browser to allow me to continuously improve the script.
mermaid-cli
Command line tool for the Mermaid library
Barbershop
Barbershop: GAN-based Image Compositing using Segmentation Masks (SIGGRAPH Asia 2021)
gateio-crypto-trading-bot-binance-announcements-new-coins
This is a crypto trading bot that scans the Binance Annoucements page for new coins, and places trades on Gateio
Senior-Dev-Roadmap
The Ultimate Python Developer Roadmap✨
DeepSeek-Math
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
awesome-trilium
A collection of interesting Trilium Notes extensions. Including themes, widgets, scripts, API extensions, etc. Trilium插件合集
OptimalPortfolio
An open source library for portfolio optimisation
portfolioopt
Financial Portfolio Optimization Routines in Python
wunderground-sensehat
Tutorial and code for using the Raspberry PI Sense HAT plus a weather API (Dark Sky) to create a personal weather dashboard.
github-mermaid-extension
A browser extension for Chrome, Opera & Firefox that adds Mermaid language support to Github
selenium_with_python
selenium with python from basic to advanced with python 3.x
danish-foundation-models
A project for training foundational Danish language model
python-collections-budget
In this project we’ll process spending data into different types of Python collections. Then we’ll use those collections to graph our spending categories and budget outcomes.