Stars
Notes from books and other interesting things that I've read. Table of contents at the end 👇
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…
Stock options, RSUs, taxes — read the latest edition: www.holloway.com/ec
📚 A curated collection of links for cryptoeconomists
Mastering Bitcoin 3rd Edition - Programming the Open Blockchain
🔑 stateless open source password manager
The JavaScript Drag & Drop library your grandparents warned you about.
A lightweight Mac OSX app to track the prices of cryptocurrency
Perform data science on data that remains in someone else's server
A system for quickly generating training data with weak supervision
University of Waterloo ECE254 Operating Systems and System Programming Lab Starter Files and Documentations
A MNIST-like fashion product database. Benchmark 👇
A collection of awesome penetration testing resources, tools and other shiny things
Bootstrap yourself to write an OS from scratch. A book for self-learner.
A collection of (mostly) technical things every software developer should know about
Python Data Science Handbook: full text in Jupyter Notebooks
Bot Framework provides the most comprehensive experience for building conversation applications.
120+ interactive Python coding interview challenges (algorithms and data structures). Includes Anki flashcards.
Bridging Spotify and macOS Notification Center
Minimal and clean examples of machine learning algorithms implementations
The most cited deep learning papers