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36 lines
931 B
Markdown
36 lines
931 B
Markdown
# N_Network
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Neural Network implementation based on the Andrew Ng courses
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Implements Batch GD, Stochastic GD (minibatch_size=1) & Stochastic minibatch GD:
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- Cost function: Cross Entropy Loss
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- Activation functions: relu, sigmoid, tanh
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- Regularization: l2 (lambd), Momentum (beta), Dropout (keep_prob)
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- Optimization: Minibatch Gradient Descent, RMS Prop, Adam
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- Learning rate decay, computes a factor of the learning rate at each # of epochs
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- Fair minibatches: Can create batches with the same proportion of labels 1/0 as in train data
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Restriction:
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- Multiclass only with onehot label
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## Install
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```bash
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pip install git+https://github.com/doctorado-ml/NeuralNetwork
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```
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## Example
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#### Console
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```bash
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python main.py
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```
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#### Jupyter Notebook
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[](https://colab.research.google.com/github/Doctorado-ML/NeuralNetwork/blob/master/test.ipynb) Test notebook
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