As I have done this presentation already several times and got a good feedback, I’m posting here the slides and some useful links that allowed me to learn and understand DL better.
And some of the great resources I’d like to share
IBM Watson platform:
https://console.bluemix.net/catalog/?category=ai
How to run your own .py file in WML
https://github.ibm.com/asood/PredictiveModeling/blob/dev/ml_dlaas_e2e_example.md
How to run your own scripts in WML using watson-machine-learning-client
https://dataplatform.ibm.com/analytics/…..
How to augment WCS-based chatbot with off topic chat based on RNN
https://towardsdatascience.com/personality-for-your-chatbot-with-recurrent-neural-networks-2038f7f34636
Watson Beat
https://www.youtube.com/watch?v=Z5ymVzTUU6Y
https://github.com/cognitive-catalyst/watson-beat
Watson Beat article on Medium
https://medium.com/@anna_seg/the-watson-beat-d7497406a202
Yolo Darkflow
https://github.com/thtrieu/darkflow
Understanding LSTM Networks
http://colah.github.io/posts/2015-08-Understanding-LSTMs/
Deep Learning for NLP Best Practices
http://ruder.io/deep-learning-nlp-best-practices/
Stanford Lectures Collection – NLP with Deep Learning 2017
https://www.youtube.com/playlist?list=PL3FW7Lu3i5Jsnh1rnUwq_TcylNr7EkRe6
Deep Learning Specialization (available also in Coursera)
https://www.youtube.com/channel/UCcIXc5mJsHVYTZR1maL5l9w
Matrix.io and Blockchain with Deep Learning
https://www.matrix.io/html/MATRIXTechnicalWhitePaper.pdf
And many others that you will find online, which I didn’t mention..
Sasha Lazarevic
July 2018