An augmentation based deep neural network approach to learn human driving behavior
Overview In this post, we will go over the work I did for project 3 of Udacity’s self-driving car project, behavior cloning for driving. The main task is to drive a car around in a simulator on a race track, and then use deep learning to mimic the behavior of human. This is a very interesting problem because it is not possible to drive under all possible scenarios on the track, so the deep learnin
Finding the genre of a song with Deep Learning — A.I. Odyssey part. 1
A step-by-step guide to make your computer a music expert. If you like Artificial Intelligence, subscribe to the newsletter to receive updates on articles and much more! One of the things we, humans, are particularly good at is classifying songs. In just a few seconds we can tell whether we’re listening to Classical music, Rap, Blues or EDM. However, as simple as this task is for us, millions of p
ResNets, HighwayNets, and DenseNets, Oh My!
When it comes to neural network design, the trend in the past few years has pointed in one direction: deeper. Whereas the state of the art only a few years ago consisted of networks which were roughly twelve layers deep, it is now not surprising to come across networks which are hundreds of layers deep. This move hasn’t just consisted of greater depth for depths sake. For many applications, the mo
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