semvec/pypi-packages huggingface dataset:
customneuralnet 1.0.6
Custom Neural Networks
Requires Python: >=3.6

# Custom Neural Networks
* Create a customized Feedforward Neural Network by changing the number of layers, activation functions, loss function and optimizer.
* Refer to the documentation of any class/method by using help(class/method) Eg: help(FNN)
* Please refer to this [repo](https://github.com/Taarak9/Neural-Networks) for more information.

## Installation
```bash
$ [sudo] pip3 install customneuralnet
``` 
## Usage
```python3
>>> from customneuralnet import FNN
```
### Creating a Feedforward Neural Network
```python3
# number of input nodes
n_inputs = 27
loss_fn = "ce"
nn = FNN(n_inputs, loss_fn)

# Add a layer with 9 nodes and activation function ReLU
nn.add_layer(9, "relu")
# Add a layer with 3 nodes and activation function sigmoid
nn.add_layer(3, "sigmoid")

# Note the last layer you added will be the output layer of the NN
# Compile the nn
# nn.compile(training_data, epochs, mini_batch_size, eta, gamma=None, optimizer="GD", mode="batch", shuffle=True, test_data, task="classification")
```
* Refer to the [Handwritten digit recognizer](https://github.com/Taarak9/Handwritten-Digit-Recognition/blob/main/src/FNN/hdr_fnn.ipynb) built using this package.