Presentation briefly introducing deep learning and how to apply a specific subset of deep learning, recurrent neural networks, to solve real world problems.
Topics covered:
- basics of supervised learning and classification
- perceptrons
- neural networks
- recurrent neural networks
- cell states (LSTM and GRU networks)
- building computation graphs in Tensorflow
- building, training and running RNNs in Tensorflow
There is a workshop that accompanies this talk. The workshop involves building the RNN architecture discussed in the talk to generate Shakespearean text.
You can also run the presentation on a local web server. Clone this repository and run the presentation like so:
npm install
grunt serve
The presentation can now be accessed on localhost:8080. Note that this web application is configured to bind to hostname 0.0.0.0, which means that once the Grunt server is running, it will be accessible from external hosts as well (using the current host's public IP address).
Huge credit to Martin Görner for his awesome Tensorflow RNN Shakespere talk, which inspired a lot of the code in this talk/workshop.