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Congratulation to DeepMind! This is a reengineering implementation (on behalf of many other git repo in /support/) of DeepMind's Oct19th publication: [Mastering the Game of Go without Human Knowledge]. The supervised learning approach is more practical for individuals. (This repository has single purpose of education only)
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Free Resources For Data Science created by Shubham Kumar
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An experiment about re-implementing supervised learning models based on shallow neural network approaches (e.g. fastText) with some additional exclusive features and nice API. Written in Python and fully compatible with Scikit-learn.
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An Architecture Combining Convolutional Neural Network (CNN) and Linear Support Vector Machine (SVM) for Image Classification
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Supplementary material for Hands-On Machine Learning with R, an applied book covering the fundamentals of machine learning with R.
🚤 Never spend O(n) to annotate data again. Fun and precision come free.
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(Moved from PyTorchLightning/pytorch-lightning#8110.)
It would be useful to have a DM for https://www.tensorflow.org/datasets/catalog/emnist.
Motivation
EMNIST is a much better dataset than MNIST, since it has more classes (0-9, a-z, A-Z), more data (4x), and more inherent ambiguity, yet it still easy to deal with computationally.
![image](https://user-i