Hi Peter!

Occasionally Medium sends me an email letting me know that people have followed my posts or maybe even liked them, which always feels great.

But I got a special treat a few days ago when one of the headshots that popped up in the “New Followers” email was Peter Norvig.

Peter Norvig is Director of Research at Google, but to me and many other engineers he is first-and-foremost the co-author of Artificial Intelligence: A Modern Approach. This was the seminal textbook of artificial intelligence in my undergraduate days. To judge by Amazon rankings, the book maintains that position today.

So Peter, if you’re reading this, thanks for the lessons and for your out-sized contributions to computer science.

Also, I followed you back. 🙂

Deep Learning

I have been studying a little bit about deep learning recently, and hope to learn more over the next week.

In particular, I have been progressing through NVIDIA’s introductory Deep Learning course, which offers an overview of Deep Neural Networks (DNNs). The course covers three DNN frameworks (Caffe, Theano, and Torch) and one visualization tool (DIGITS).

This type of course is super-helpful, in that it’s geared toward practitioners and problem-solving, and less on the theory of DNNs. The Caffe framework, combined with the DIGITS visualization tool, seems particularly well-suited to quickly constructing a DNN and seeing where it leads.

So I’m a big fan of the NVIDIA course.

Next I’d like to take either Coursera’s Neural Networks for Machine Learning, or Udacity’s Deep Learning.

Coursera’s course is taught by the famed neural network researcher Geoffrey Hinton, whereas Udacity’s courses have a great UI and often a more practical (versus theoretical) approach.

I’ll let you know what I choose, and let me know if you have any recommendations!