What would the sky look like if Mars, Jupiter, Saturn, or Neptune were as close to us as the Moon is now? Well, other than the global calamity caused by extreme tides and general astrophysical disruption, it looks quite pretty. If Planets were as close as the Moon pic.twitter.com/bBwIPtRQ1J — … Read moreBecause it’s Friday: If planets were as close as the moon
So it turns out that the 1990 Michael Crichton novel Jurassic Park is, indeed, a work of fiction. (Personal note: despite the snark to follow, the book is one of my all-time favorites — I clearly remember devouring it in 24 hours straight while ill in a hostel in France.) … Read moreSimulating dinosaur populations, with R
Image File Format Any images are stored in memory, raster image contain pixel values arrange in regular matrix. Conversely, vector image represent geometric objects using continuous coordinates. If you scale up the raster image,resolution of the image will be lost but it does not happen in vector image. Raster image and … Read moreImage Processing Class #0.2 — Digital Image
Nov 29, 2018 The rapid rise in AI applications, decreasing processor and memory costs have allowed the last decade to show incredible progress with Recommender Systems. Given their rising importance in the retail industry, they are undoubtedly one of the more popular topics in Artificial Intelligence. https://thedatascientist.com/wp-content/uploads/2018/05/recommender_systems.png However, creating a … Read moreFull-Fledged Recommender System
Dada, Instagram, and the future of AI Collage is the language of the moment, but has been for over 100 years. Lets walk through where it came from (Dada), what it’s up to now (Instagram), and why it’s integral to the future of AI (Deep Fakes, GANS, and the ingrained copy). … Read moreWe are Collage
Nov 29, 2018 TL;DR: In this article you’ll learn how to implement sequence-to-sequence models with and without attention on a simple case: inverting a randomly generated sequence. You might already have come across thousands of articles explaining sequence-to-sequence models and attention mechanisms, but few are illustrated with code snippets. Below is … Read moreAttention Seq2Seq with PyTorch: learning to invert a sequence
Nov 27, 2018 In this series of articles I will explain the inner workings of a neural network. I will lay the foundation for the theory behind it as well as show how a competent neural network can be written in few and easy to understand lines of Java code. … Read morePart 1: A neural network from scratch — Foundation
How art and wanting to change the world led me to data science Nov 27, 2018 Data plays a crucial role in understanding the world around us. I’ve been working with data in one way or another since before I could appreciate its value. Now I’m in an immersive data science … Read moreWhat better time than now?
Nov 27, 2018 I recently leveled up to fatherhood. That’s why I am currently on 5 months of parental leave (thank’s to the awesome team @store2be for going along with this!). Every morning at around 5am, I leave the bedroom with my son for the kitchen so his mom can … Read moreMap the solar system to a place near you –A NatGeo’s MARS inspired Shiny web app
This is the next article in my series on AzureR, a family of packages for working with Azure in R. I’ll give a short introduction on how to use AzureVM to manage Azure virtual machines, and in particular Data Science Virtual Machines (DSVMs). Creating a VM Creating a VM is … Read moreAzureVM: managing virtual machines in Azure