Datasets for Computer Vision

The dataset is an integral part of an ML engineer’s toolkit. We recently compiled useful information about a range of these well known datasets. It’s all in one place, and hopefully useful to others as well.
Deep Learning Frameworks

Choosing a Machine Learning Framework in 2018

There are plenty of established machine learning frameworks out there, and new frameworks are popping up frequently to address specific niches. We were interested in examining if one of these frameworks fits in our workflow. I surveyed the most popular frameworks, and aim to provide a helpful comparative analysis.

New approaches to Deep Networks – Capsules (Hinton), HTM (Numenta), Sparsey (Neurithmic Systems) and RCN (Vicarious)

  Reproduced left to right from [8,10,1] Within a 5 day span in October, 4 papers came out that take a significantly different approach to AI hierarchical networks. They are all inspired by biological principles to varying degrees. It’s exciting to see different ways of thinking. Particularly at a time… Read More »New approaches to Deep Networks – Capsules (Hinton), HTM (Numenta), Sparsey (Neurithmic Systems) and RCN (Vicarious)

Reading list – October 2017

This month’s reading list has two parts: a non-Reinforcement Learning list, and a Reinforcement Learning list. Since our next blog post will be on Reinforcement Learning, readers might like to refer to our RL reading list separately. Non-Reinforcement Learning reading list A Framework for searching for General Artificial Intelligence Authors:… Read More »Reading list – October 2017