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3d-shapes

This repository contains the 3D shapes dataset, used in Kim, Hyunjik and Mnih, Andriy. "Disentangling by Factorising." In Proceedings of the 35th International Conference on Machine Learning (ICML). 2018. to assess the disentanglement properties of unsupervised learning methods.

adversarial-robustness-toolbox

Python library for adversarial machine learning (evasion, extraction, poisoning, verification, certification) with attacks and defences for neural networks, logistic regression, decision trees, SVM, gradient boosted trees, Gaussian processes and more with multiple framework support

book-resources

cleverhans

An adversarial example library for constructing attacks, building defenses, and benchmarking both

code_snippets

codeforces

competitive_prog

db_proj

deep-math-machine-learning.ai

A blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.

deepfool

A simple and accurate method to fool deep neural networks

deeplearning-models

A collection of various deep learning architectures, models, and tips

deeplearningmovies

Kaggle's competition for using Google's word2vec package for sentiment analysis

disentanglement_lib

disentanglement_lib is an open-source library for research on learning disentangled representations.

docs

TensorFlow documentation

ds-cheatsheets

List of Data Science Cheatsheets to rule the world

foolbox

Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, Keras, …

geospatial-queries

google-chrome-dino-game-ai

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

html-dom-document-object

javascript

learning javascript

kaggle-api

Official Kaggle API

kaggle_earthquake_challenge

This is the code for the Kaggle Earthquake Challenge by Siraj Raval on Youtube

logistic-reg

Logistic regression from scratch with NumPy

mail-spam-filtering

It uses machine learning models (Multinomial NB & SVM) to predict whether the email is spam or ligitimate on two corpus namely Ling-spam corpus and Euron-spam corpus.

manip-ml

Code for the IEEE S&P 2018 paper 'Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning'

mannequinchallenge

Inference code and trained models for "Learning the Depths of Moving People by Watching Frozen People."

map

mathematics-of-deep-learning

The Mathematics of Deep Learning, SIPB IAP 2018

mean-stack