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Deep Neural Network with NumPy

This project is an implementation of a deep neural network using only NumPy. It supports both classification and regression problems, minibatch training, and customizable network depth and activation functions.

Setup

  1. Clone the repository: 
    git clone <repository-url>
  2. Create Virtual Environment: 
    python3 -m venv ~/.venv_dnn
source ~/.venv_dnn/bin/activate
  3. Install Dependencies: 
    pip3 install numpy

Usage

Navigate to the project directory and run prog1.py with the necessary command-line arguments:

python prog1.py [-v] -train_feat TRAIN_FEAT_FN -train_target TRAIN_TARGET_FN -dev_feat DEV_FEAT_FN -dev_target DEV_TARGET_FN -epochs EPOCHS -learnrate LEARNRATE -nunits NUM_HIDDEN_UNITS -type PROBLEM_MODE -hidden_act HIDDEN_UNIT_ACTIVATION -init_range INIT_RANGE [-num_classes C] [-mb MINIBATCH_SIZE] [-nlayers NUM_HIDDEN_LAYERS]