How to Apply Deep Learning to Real-World Problems
Deep Learning is a new area of Machine Learning research, which has been introduced with the objective of moving Machine Learning closer to one of its original goals: Artificial Intelligence.
Join Jennifer Marsman as she welcomes Sonja Knoll to the show as they take a deep dive into Deep Learning as well as apply some real-world scenarios for you to try out on your own.
Looking for more information? Check out the following links below:
- Deep Learning – give it a try! Try the app http://CaptionBot.ai – works for any browser/phone
Call the Microsoft Cognitive Services API https://www.microsoft.com/cognitive-services
Build you own cool deep model on CNTK https://github.com/Microsoft/CNTK
- Deep Learning
Generalization and Network Design Strategies by Lecun, Y., Technical Report CRG-TR-89-4, University of Toronto, 1989
Learning representations by back-propagating errors by Rumelhart, D., Hinton, G., and Williams, R., Nature 323, 533–536, 1986
- Blog: The Unreasonable Effectiveness of Recurrent Neural Networks by Andrej Karpathy
Long Short-Term Memory by Hochreite, S., and Schmidhuber J., Neural Computation 9(8): 1735-1780, 1997
Blog: Understanding LSTM Networks by Christopher Olah
If you're interested in learning more about the products or solutions discussed in this episode, click on any of the below links for free, in-depth information:
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