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ML-Study

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kkozistr committed 6 years ago
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kkozistr committed 6 years ago
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kkozistr committed 6 years ago
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kkozistr committed 6 years ago
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kkozistr committed 6 years ago
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kkozistr committed 6 years ago

README

The README file for this repository.

Machine Learning Studies

  1. Stanford CS231n Winter 2016 : Convolutional Neural Networks for Visual Recognition - Done

  2. Stanford CS20 2018 : Tensorflow for Deep Learning Research - Continue

  3. Stanford CS229 2017 : Machine Learning

  4. Oxford CS deepnlp 2017 : https://github.com/oxford-cs-deepnlp-2017/lectures

  5. NOTRE DAME Statistical Computing 2017 : https://www.zabaras.com/statisticalcomputing

  6. Read http://efavdb.com/gaussian-processes/ - Done

  7. Check http://blog.dlib.net/2017/12/a-global-optimization-algorithm-worth.html - Done

  8. Read https://ratsgo.github.io/blog/categories/

  9. Implement Awesome-GANs : https://github.com/kozistr/Awesome-GANs/ - Done, Continue

  10. Implement Object Detection with Yolo v2 & Faster R-CNN for embedded devices - Pending

  11. Find about Real-Time Image Captioning for embedded devices - Done

  12. Kaggle : Plant Seedlings Classification - Done

  13. Write a kernel, Kaggle : Plant Seedlings Classification - Done

  14. Find about WaveNet, sound classification(?), generation - Done, Continue

  15. https://github.com/jtoy/awesome-tensorflow

  16. Sound Classification & Pre-Processing... - Continue

  17. Check Yolo v3 - Done