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icml2016

Generative Adversarial Text-to-Image Synthesis

icml2020-stochastic-iterative-target-augmentation

igan

Interactive Image Generation via Generative Adversarial Networks

ilearndeeplearning.py

This repository contains small projects related to Neural Networks and Deep Learning in general. Subject are closely linekd with articles I publish on Medium. I encourage you both to read as well as to check how the code works in the action.

illustrationgan

A simple, clean TensorFlow implementation of Generative Adversarial Networks with a focus on modeling illustrations.

image-gpt

imd

The Shape of Data: Intrinsic Distance for Comparing Data Distributions

imdbpy

IMDbPY is a Python package useful to retrieve and manage the data of the IMDb movie database about movies, people, characters and companies. This is a git clone of the official Mercurial repository.

improved-gan

code for the paper "Improved Techniques for Training GANs"

improved_wgan_training

Code for reproducing experiments in "Improved Training of Wasserstein GANs"

incremental-representation-learning

Incremental vertex representation learning using random walks and skip-gram model.

industry-machine-learning

A curated list of applied machine learning and data science notebooks and libraries across different industries.

innvestigate

A toolbox to iNNvestigate neural networks' predictions!

insight_project_shv

inspect_word2vec

Python code for checking out Google's pre-trained, 3M word Word2Vec model

instagram_like_predictor

intergraph

R package for converting network data objects between different classes

interpret

Fit interpretable models. Explain blackbox machine learning.

interpretability_blog

The notebooks used to demonstrate the blog post about Interpretability in ML

interpretable-ml-book

Book about interpretable machine learning

interpretable_machine_learning_with_python

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

interpreting-neural-networks

A few iPython notebooks on interpretation of neural networks

intro_to_the_math_of_intelligence

This is the code for "Intro - The Math of Intelligence" by Siraj Raval on Youtube

introduction_move37

This is the code for "Introduction (Move 37)" By Siraj Raval on Youtube

invariantcausal.jl

Causal Inference with Invariant Prediction

invariantcausalprediction

:exclamation: This is a read-only mirror of the CRAN R package repository. InvariantCausalPrediction — Invariant Causal Prediction

invariantriskminimization

PyTorch code to run synthetic experiments.

invasive-ductal-carcinoma-cnn

invent-prediction

Model to accurately forecast inventory demand based on historical sales data.

inventorbot