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…

The TensorFlow blog contains regular news from the TensorFlow team and the community, with articles on Python, TensorFlow.js, TF Lite, TFX, and more.

AR-Net is a new framework that combines the best of both traditional statistical models and neural network models for time series modeling. The feed forward model is not only as interpretable as AR models but is also scalable and easier to use.

The Bayes Optimal Classifier is a probabilistic model that makes the most probable prediction for a new example. It is described using the Bayes Theorem that provides a principled way for calculating a conditional probability. It is also closely related to…

Facebook AI is releasing a novel approach to cooperative multi-agent reinforcement learning, that assigns tasks to individual agents, making them better at generalizing to more complex situations

Netflix open-sources its human-friendly Python Framework 'Metaflow' to build and manage real-life data science projects with ease. Metaflow was originally developed at Netflix for addressing the needs of its data scientists who work on demanding real-life…