Skip to main content

Custom Deep Learning

Project description

Custom Deep Learning

  • 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 for more information.

Installation

$ [sudo] pip3 install customdl

Development Installation

$ git clone https://github.com/Taarak9/Custom-DL.git

Usage

>>> from customdl import FNN

Creating a Feedforward Neural Network

# 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, test_data)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

customdl-1.0.7.tar.gz (6.6 kB view hashes)

Uploaded Source

Built Distribution

customdl-1.0.7-py3-none-any.whl (7.1 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page