EasyNN 0.0.20

EasyNN is a python package designed to provide an easy-to-use Neural Network. The package is designed to work right out of the box with multiple datasets, while also allowing the user to customize features as they see fit.

EasyNN - Neural Networks made Easy

EasyNN is a python package designed to provide an easy-to-use Neural Network. The package is designed to work right out of the box with multiple datasets, while also allowing the user to customize features as they see fit.

Requires Python version 3.9.7 or greater.

Check out our wiki for more information.

Installation:

Run python's pip3 to install:

pip3 install EasyNN

Getting started with EasyNN(Basic Example):

To see more documention please see our wiki's infomation on the number mnist dataset.

from EasyNN.dataset.mnist.number import trained_model, dataset, show

# Downloads dataset to computer
train_data,train_labels,test_data,test_labels = dataset

# Grab a training data image
image = test_data[0]

# Uses the EasyNN train model on an example test image.
print(trained_model(image))

# Show the image
show(image, "image")

Output:

Downloading Trained MNIST model...
Download complete.
Downloading number_train-images-idx3-ubyte.gz...
Downloading number_t10k-images-idx3-ubyte.gz...
Downloading number_train-labels-idx1-ubyte.gz...
Downloading number_t10k-labels-idx1-ubyte.gz...
Download complete.
Save complete.
7

Image output:

Future goals for non known datasets:

from EasyNN.model import model

xtrain = "My images"
ytrain = "My labels"

model.dataset = xtrain, ytrain

model(xtrain[0])