Pinned Repositories
AI-reading-list
Up to date list of the most interesting papers in AI
deeplearning-models
A collection of various deep learning architectures, models, and tips
explaindebug
fairml
high_performance_python
Code for the book "High Performance Python" by Micha Gorelick and Ian Ozsvald with OReilly
infembed
posthocspurious
reinforcement-learning
Minimal and Clean Reinforcement Learning Examples
sanity_checks_saliency
infembed
Find the samples, in the test data, on which your (generative) model makes mistakes.
adebayoj's Repositories
adebayoj/fairml
adebayoj/sanity_checks_saliency
adebayoj/explaindebug
adebayoj/posthocspurious
adebayoj/infembed
adebayoj/high_performance_python
Code for the book "High Performance Python" by Micha Gorelick and Ian Ozsvald with OReilly
adebayoj/reinforcement-learning
Minimal and Clean Reinforcement Learning Examples
adebayoj/deeplearning-models
A collection of various deep learning architectures, models, and tips
adebayoj/lectures
Oxford Deep NLP 2017 course
adebayoj/papers_talks
adebayoj/path_explain
A repository for explaining feature attributions and feature interactions in deep neural networks.
adebayoj/Bios8366
Advanced Statistical Computing at Vanderbilt University's Department of Biostatistics
adebayoj/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
adebayoj/DoubleReinforcementLearningMDP
adebayoj/DP-AGD
Concentrated Differentially Private Gradient Descent with Adaptive per-iteration Privacy Budget
adebayoj/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.
adebayoj/gitignore
A collection of useful .gitignore templates
adebayoj/GradingKneeOA
Knee osteoarthritis analysis with X-ray images using CNN
adebayoj/html_parsing_whatsapp
adebayoj/indigo
:ramen: Minimalist Jekyll Template
adebayoj/influencedisparity
adebayoj/interview
Interview questions
adebayoj/naija_talks
adebayoj/PRML-Solution-Manual
my own Solution Manual of PRML
adebayoj/python-causality-handbook
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and sensitivity analysis.
adebayoj/reinforcement-learning-an-introduction
Python Implementation of Reinforcement Learning: An Introduction
adebayoj/rsna-boneage-ossification-roi-detection
adebayoj/Self-Tuning-Networks
PyTorch implementation of "STNs" and "Delta-STNs"
adebayoj/talk_files
adebayoj/You-Dont-Know-JS
A book series on JavaScript. @YDKJS on twitter.