OpenNMT-tf is a neural machine translation toolkit for TensorFlow released in 2017. At that time, the project used many features and capabilities offered by TensorFlow: training and evaluation with tf.estimator, variable scopes, graph collections, tf.contrib…

Fitting a model to a training dataset is so easy today with libraries like scikit-learn.

A model can be fit and evaluated on a dataset in just a few lines of code. It is so easy that it has become a problem.

The same few lines of code are repeated again…

Google Research. Contribute to google-research/google-research development by creating an account on GitHub.

We are making available the DeepFovea network architecture, a new state of the art in foveated rendering for augmented and virtual reality using an AI-powered system.

Uber introduces Hypothesis GU Func, a new extension to Hypothesis, as an open source Python package for unit testing.

Machine learning and deep learning models, like those in Keras, require all input and output variables to be numeric. This means that if your data contains categorical data, you must encode it to numbers before you can fit and evaluate a model. The two most…

In this tutorial, you will learn how to detect fire and smoke using Computer Vision, OpenCV, and the Keras Deep Learning library.

The lottery ticket hypothesis suggests that by training DNNs from “lucky” initializations, we can train networks which are 10-100x smaller with minimal performance losses. In new work, we extend our understanding of this phenomenon in several ways.

What is an exoplanet? How do we find them? Most importantly, why do we want to find them? Exoplanets are planets outside of our Solar System - they orbit any star other than our Sun.



We can find these exoplanets via a few methods: radial velocity, transits…

Learn more about LIGHT, a new large-scale fantasy text adventure game that enable researchers to study language and actions jointly in a game world.

An empirical distribution function provides a way to model and sample cumulative probabilities for a data sample that does not fit a standard probability distribution.

As such, it is sometimes called the empirical cumulative distribution function, or ECDF…

This repository contains implementations and illustrative code to accompany DeepMind publications - deepmind/deepmind-research

This study uses video and a pretrained deep convolutional neural network to analyze facial photoplethysmographic signals in detection of atrial fibrillation.

Given easy-to-use machine learning libraries like scikit-learn and Keras, it is straightforward to fit many different machine learning models on a given predictive modeling dataset. The challenge of applied machine learning, therefore, becomes how to choose…