Day 9 of Machine Learning in Review

Resources explored

• 7 Companies Using Blockchain To Power AI Applications

  More explicitly this looks at 7 companies exploring this new frontier at the intersection of blockchain, AI, and data marketplaces.

  I love what most of these companies propose, although at the moment their selling point might be on the part of exposing data that wouldn’t normally be exposed. I guess this is where my limitations are at the moment.

  Although I am confident these companies are serious and already have something on the market, their infrastructure and data exchanges seem to be under development, but the prospect of early involvement can be quite enticing.

• What a GAN is

  This Wiki link is worth it as this higher order concept leads to many other definitions that are worth keeping an account of. However, this wikipedia page is lacking, the next guide paints a way better picture.

• A Beginner’s Guide to Generative Adversarial Networks (GANs)

• Using Unsupervised Learning to plan a vacation to Paris: Geo-location clustering

• Deep Dive into Math Behind Deep Networks

  This is enough to start on the Maths behind: Single neuron, Single layer

Tools Encountered

• Deep Learning for Java

  Although I am not the biggest fan of Java, this library comes in handy for some notions, the examples are quite useful. Between them, MLP Neural Nets, Convolutional Neural Nets and
  Recurrent Neural Nets interest me as I would not know enough about them or the others at this point.

• Distractor-aware Siamese Networks for Visual Object Tracking

• Simple and flexible progress bar for Jupyter Notebook and console