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archivine

funky readme

awesome-tmux

A list of awesome resources for tmux

blog

Welcome to my blog! the place where I'll learn, share and practice writing the blog.

d2l-en

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

deeplake

Data Lake for Deep Learning. Build, manage, query, version, & visualize datasets. Stream data real-time to PyTorch/TensorFlow. https://activeloop.ai

dotfiles

:wrench: .files, including ~/.macos — sensible hacker defaults for macOS

effective-pandas

Source code for my collection of articles on using pandas.

effective_pandas_book

Errata and code for Effective Pandas book

hello-github

:octocat: Introduction to Git and Github Workshop for https://devahoy.com

masendor

Educational and historical wargame

nanogpt

The simplest, fastest repository for training/finetuning medium-sized GPTs.

ng-video-lecture

nlp-datasets

Alphabetical list of free/public domain datasets with text data for use in Natural Language Processing (NLP)

nvim

Neovim 0.8 configuration for coding React and TypeScript

pandas-workshop

An introductory workshop on pandas with notebooks and exercises for following along.

pure

Pretty, minimal and fast ZSH prompt

python

This repository helps you understand python from the scratch.

python-for-probability-statistics-and-machine-learning

Jupyter Notebooks for Springer book "Python for Probability, Statistics, and Machine Learning"

springboardcapstone_yelpanalysis

Code for Springboard Capstone Project -- Analyzing 2 proposed tweaks to the Yelp rating system

tinygrad

You like pytorch? You like micrograd? You love tinygrad! ❤️

tinyvoice

Letting computers listen to you and really care

tmux

An arctic, north-bluish clean and elegant tmux color theme.

top-github-users

Check your ranking in GitHub! Don't forget to star ⭐ this repository.

weather-website-flask

web-scraping-nba-statistics

Use Python to scrape ESPN for stats on all players in the NBA. Obtain and organize data, calculate statistics, and model using urllib, re, pandas, and scikit-learn.