Deep Learning Textbook Chapter 2: Probability
As part of the Max Planck Centre’s Deep Learning reading group, I’m working my way through the soon-to-be released Deep Learning textbook. These posts are my informal notes for each chapter. Find my notes from chapter 1 here. Thanks again to Zeb & Toby for edits. This week we were back on slightly firmer ground, dealing \[…\]
Deep Learning Textbook Chapter 1: Linear Algebra
The Dolan lab group (and friends) is working through the soon-to-be-released Deep Learning textbook, authored by Goodfellow Bengio, and Courville, and somewhat miraculously available in html form prior to publication by MIT press. At a risk of exposing the depths of my ignorance to the internet, I’m going to try and publish my notes on each chapter \[…\]
Setting up Tensorflow for Mac OS X
Alternative method from the Asimov institute. This worked fine for me using an Anaconda install of Python on Mac OS X, except I had to remove the ‘–update’ flag when doing the installation with pip. Their version involves direct installation on OS X rather than installation on a virtual Linux machine via Docker, which is \[…\]
The Happiness Project
The Happiness Project is a project I’ve been involved in for just over two years, which began as a low-key attempt to explore why a UNICEF report found British children to be very unhappy relative to children in similar countries and blew up into a show involving 12 young adults and 6 academics performed at the Edinburgh festival.
What’s the deal with modafinil?
Scientists need to stop hyping smart drugs. We don’t know if or how they work and what the long term consequences of use might be.
Running deep reinforcement learning models
Deep Mind’s Nature paper has created an understandable buzz. In it they create an algorithm than can learn to play a huge slew of Atari computer games better than a human expert. Particularly compelling are the videos, which I encourage you to check out. One delightful feature of the paper is that they provide the \[…\]