Atma Mani, a geospatial engineer for ESRI, imagined shopping for a house with data, maps, and analysis. Basically, a personalized recommendation system:

by Angelika Stefan & Felix Schönbrodt

In recent years, a specific machine learning method called deep learning has gained huge attraction, as it has obtained astonishing results in broad applications such as pattern recognition, speech recognition, computer vision, and natural language processing. Recent research has also been shown that deep learning techniques can be combined with reinforcement learning methods to learn useful representations for the problems with high dimensional raw data input. This chapter reviews the recent advances in deep reinforcement learning with a focus on the most used deep architectures such as autoencoders, convolutional neural networks and recurrent neural networks which have successfully been come together with the reinforcement learning framework. Deep Reinforcement Learning: An Overview

The Matrix Normal Distribution (matrixNormal)Computes densities, probabilities, and random deviates of the Matrix Normal (Iranmanesh et.al. (2010) <doi:10.7508/ijmsi.2010.02.004>). Also incl …

Imagining an Engineer: On GAN-Based Data Augmentation Perpetuating Biases

A re-tweet from a colleague whom I follow on Twitter brought an important paper to my attention. I thought I’d share it more widely.

By Assaf Katan, Apertio CEO & Co-Founder

In this blog post, I will show you how you can quickly and easily forecast a univariate time series.I am going to use data from the EU Open Data Portal on air passenger transport. You can find thedata here. I downloadedthe data in the TSV format for Luxembourg Airport, but you could repeat the analysis for any airport.

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