Deep Learning Teaching Resources What would you recommend as the best resources for learning and teaching about Deep Learning?  These could include tools (e.g. TensorFlow), tutorials, books (e.g. Deep Learning), MOOCs (e.g. Udacity's), etc.

I'm working to put together a list of best resources for an upcoming issue of AI Matters. What I'm looking for is the best of the best entry points into an understanding of deep learning. Nothing even so specific as convolutional networks is necessary. As an educator, I am motivated to collect and share the best first footholds for giving students and professionals a start for the mighty climb that is highly motivated by recent achievements. As far as audience, I envision undergraduate intro AI through adult professional.
The first thing that must be discussed in the matter, is the mathematics involved. 

Deep learning is first and foremost a mathematical model. An overview of this big subject is given quite well in its Wikipedia article. The page showcases a summary of the subject, as well as links to more resources (2 birds in 1 go).  

To explain the mathematical model, I recommend reading this article. This gives a relatively good basis of understanding for neural networks (which are a "supertype" of deep learning algorithm). Afterwards, page 4 of the article is a good place from which to progress towards Deep learning. For example, the neural network in the image from that page:



But what if we had more than 1 hidden layer? Now that's classified as deep learning. 

A short google search for "deep learning neural networks" gives this handy website. It, too, gives a brief summary of the mathematics, increasing understanding. 

After reading these articles and that website, you and your students should be good to go, and start gaining hands-on experience. Usually, the basic example for a deep learning algorithm is to fit a linear function to a dataset of points.

Another article (again, found through google search) explains the subject with more specific information. I recommend reading it to gain greater understand of the subject.

Because links sometimes go broken, it might be a good idea to download those articles (they are pdf files). Then again, they were found with straight forward google searches, so that's more reliable, especially in such a quickly evolving field.