Difference between revisions of "Machine Learning Experiments"
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==Projects== | ==Projects== | ||
*[http://www.cs.toronto.edu/~ilya/rnn.html THE TEXT-GENERATING RNN DEMO by Ilya Sutskever] | *[http://www.cs.toronto.edu/~ilya/rnn.html THE TEXT-GENERATING RNN DEMO by Ilya Sutskever] | ||
*[http://www.cs.toronto.edu/~graves/handwriting.html Handwriting Demo by Alex Graves] | |||
==Learning resource== | ==Learning resource== | ||
Revision as of 22:21, 6 July 2017
References
Examples with source code
- Chinese receipt OCR using Tensorflow | SpikeFlow (Blog | Github)
- Recurrentjs by Andrej Kaparthy, mainly for text training. "Sentences are input data and the networks are trained to predict the next character in a sentence." > Re-appropriate by UCL Creative Hub
Projects
Learning resource
- Daniel Shiffman's Nature of Code: Neural networks| video
- Machine Learning for Artists by Gene Kogan and Francis Tseng
- Machine Learning A-Z™: Hands-On Python & R In Data Science
Experiments/Tests
- Running spam data in RecurrentJS
