First commit

README.md

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