Difference between revisions of "Machine Learning Experiments"
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* Daniel Shiffman's Nature of Code: [http://natureofcode.com/book/chapter-10-neural-networks/ Neural networks]| [https://www.youtube.com/watch?v=XJ7HLz9VYz0&list=PLRqwX-V7Uu6aCibgK1PTWWu9by6XFdCfh video] | * Daniel Shiffman's Nature of Code: [http://natureofcode.com/book/chapter-10-neural-networks/ Neural networks]| [https://www.youtube.com/watch?v=XJ7HLz9VYz0&list=PLRqwX-V7Uu6aCibgK1PTWWu9by6XFdCfh video] | ||
* [https://ml4a.github.io/ Machine Learning for Artists] by Gene Kogan and Francis Tseng | * [https://ml4a.github.io/ Machine Learning for Artists] by Gene Kogan and Francis Tseng | ||
* [https://www.udemy.com/machinelearning/ Machine Learning A-Z™: Hands-On Python & R In Data Science] | |||
==Experiments/Tests== | ==Experiments/Tests== | ||
Revision as of 21:36, 6 July 2017
References
Examples
- Chinese receipt OCR using Tensorflow | SpikeFlow (Blog | Github)
- Recurrentjs, mainly for text training. "Sentences are input data and the networks are trained to predict the next character in a sentence."
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