LLM101n: Let's build a Storyteller

A reinforcement learning framework based on MLX.

A collection of learning resources for curious software engineers

Various projects using Large Language Model (GPT & LLAMA) other open source model from HuggingFace and OpenAI. OpenAI API required for running various model

Practical guidance for time series analysis in Python

iPython NOtebooks on Stats

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

Lectures for Udemy - Complete Python Bootcamp Course

An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code

Deep Learning Specialization by Andrew Ng on Coursera.

Official content for Harvard CS109

Data Science Course Materials - Fall 2014

Programming exercises for the Stanford Unsupervised Feature Learning and Deep Learning Tutorial

My udemy notebooks

Lecture notes and python code to replicate models built throughout the course of Richard Mcelreath's 2023 Lecture Series 'Statistical Rethinking'. Relies on pymc

Assignments of the Udacity MOOC Deep Learning

Algorithm from The Elements of Statistical Learning book implement by Python 3 code

An interactive online reading of McElreath's Statistical Rethinking

A dump of all the data science materials (mostly pdf's) that I have accumulated over the years

Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflow 2.

Making large AI models cheaper, faster and more accessible