Difference between revisions of "Machine Learning Experiments"
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==Examples== | ==Examples== | ||
* Chinese receipt OCR using Tensorflow | SpikeFlow ([https://deeperic.wordpress.com/2017/02/18/chinese-ocr-tensorflow/ Blog] | [https://github.com/deeperic/SpikeFlow Github]) | * Chinese receipt OCR using Tensorflow | SpikeFlow ([https://deeperic.wordpress.com/2017/02/18/chinese-ocr-tensorflow/ Blog] | [https://github.com/deeperic/SpikeFlow Github]) | ||
* [https://github.com/karpathy/recurrentjs Recurrentjs], mainly for training | * [https://github.com/karpathy/recurrentjs Recurrentjs], mainly for text training. "Sentences are input data and the networks are trained to predict the next character in a sentence." | ||
==Learning resource== | ==Learning resource== | ||
Revision as of 21:33, 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