The Quartz guide to bad data
An exhaustive reference to problems seen in real-world data along with suggestions on how to resolve them.
Awesome Relation Extraction
A curated list of awesome resources dedicated to Relation Extraction, one of the most important tasks in Natural Language Processing (NLP).
A Deep Learning based project for colorizing and restoring old images
Immersive Analytics Toolkit is a Unity project to help you build high quality, interactive and scalable data visualisations in Immersive Environments (Virtual/Augmented Reality)
A platform for Applied Reinforcement Learning (Applied RL)
A python experiment management toolset created to simplify two simple use cases: design and deploy experiments in the form of python modules/files.
A Python toolkit used to train reinforcement learning algorithms against arcade games
A Pytorch implementation of “FloWaveNet: A Generative Flow for Raw Audio”
A Flow-based Generative Network for Speech Synthesis
PyTorch version of Google AI’s BERT model with script to load Google’s pre-trained models
Chainer implementation of “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding”
This project introduces an exploration bonus for deep reinforcement learning methods that is easy to implement and adds minimal overhead to the computation performed.
This is the Code for the Paper “Neural Architecture Optimization”
A distributed implementation of “graph2vec: Learning Distributed Representations of Graphs” (MLGWorkshop 2017).
Efficient Neural Architecture Search coupled with Quantized CNNs to search for resource efficient and accurate architectures.
Pervasive Attention: 2D Convolutional Networks for Sequence-to-Sequence Prediction
A lightweight implementation of Walklets from “Don’t Walk Skip! Online Learning of Multi-scale Network Embeddings” (ASONAM 2017).
This is a library for Data Pre-processing Algorithms for Streaming in Flink (DPASF)
A lightweight library for neural network graphs and training metrics for PyTorch and Tensorflow.
An Automatic Model Compression (AutoMC) framework for developing smaller and faster AI applications.