A neural network model to predict arithmetic operation results.
Overview
MathModel generates synthetic datasets of arithmetic operations (+, -, *, /) and trains a neural network to accurately predict the results of these operations.
Development
This project uses Poetry for dependency management and pytest for testing.
Installation
# Install dependencies poetry install # Install development dependencies poetry install --with dev
Usage
Train the Model
poetry run python math_model.py
Outputs
After training, the following files are created:
trained_math_model.keras— Trained neural network model.max_input_value.npy— Scaling factor used for input normalization.
Testing
You can run tests locally using:
# Run all tests poetry run pytest # Run tests with coverage and HTML report poetry run python run_tests.py --coverage --html
Continuous Integration
This project uses GitHub Actions to run tests on every push to the main branch and on pull requests.
Test Reports
Test reports are automatically generated and published to GitHub Pages after successful runs on the main branch.
