This project is a versatile neural network package specifically designed for classification tasks. It can be used for training various deep learning models, including image recognition. The package includes an example project for MNIST classification to demonstrate its capabilities. With its flexible architecture, the package is suitable for a range of classification tasks requiring deep learning, offering high accuracy and reliability.
- numpy
- matplotlib
- albumentations
- scikit-learn
- jupyter
- scipy
- scikit-image
- pillow
- customtkinter
- Clone the repository
- Navigate to the package directory
- Run
pip install .
to install package
or
- Run
pip install git+https://github.com/Havilash/Neural-Network.git#egg=neural_network
to install package
- Import package
from neural_network import activations, costs, nn as neural_network, layers, gui, constants
from neural_network.data import get_mnist_data, get_augmented_mnist_data, train_test_split
from neural_network.filters import ALL_FILTERS
- Run example project
python ./neural_network/main.py
orpython -m neural_network.main
see the LICENSE file for details