This project uses a simple linear regression model built with PyTorch to predict values using the formula y = wx + b.
- The model learns the best weight (w) and bias (b) by comparing its predictions to real data and adjusting these parameters to reduce the error.
- Training involves feeding in data, calculating how wrong the predictions are (the loss), and updating the model to improve its accuracy over time.
- The final model can make predictions on new data based on what it has learned.