Julius Adebayo's repositories
high_performance_python
Code for the book "High Performance Python" by Micha Gorelick and Ian Ozsvald with OReilly
reinforcement-learning
Minimal and Clean Reinforcement Learning Examples
deeplearning-models
A collection of various deep learning architectures, models, and tips
path_explain
A repository for explaining feature attributions and feature interactions in deep neural networks.
Caltech-Birds-Classification
This repo includes code (written in Python) for Caltech-UCSD Birds-200-2011 dataset classification. I have used PyTorch Library for CNN's. You can download the dataset here http://www.vision.caltech.edu/visipedia-data/CUB-200-2011/CUB_200_2011.tgz
EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
GradingKneeOA
Knee osteoarthritis analysis with X-ray images using CNN
PRML-Solution-Manual
my own Solution Manual of PRML
python-causality-handbook
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and sensitivity analysis.
reinforcement-learning-an-introduction
Python Implementation of Reinforcement Learning: An Introduction
Self-Tuning-Networks
PyTorch implementation of "STNs" and "Delta-STNs"
You-Dont-Know-JS
A book series on JavaScript. @YDKJS on twitter.