Deep Learning - Lab - Building and Optimizing a Feedforward Neural Network with PyTorch
About
In this lab, you will:
- Build a feedforward neural network for classifying the Iris dataset.
- Experiment with different optimizers and regularization techniques.
- Evaluate and compare model performance.
Materials We Provide
| Topic | Description | Link |
|---|---|---|
| Activity | Building and Optimizing a Feedforward Neural Network with PyTorch | Link |
Prerequisites
Before this activity, you should already be able to:
- Understand and implement regression modeling algorithms
- Understand and implement classification modeling algorithms
- Understand and interpret regression and classification metrics
- Understand the principles of feedforward neural networks
Important note
Please ignore the _layouts folder and the config.yml file in the root of this repo. They are needed to make sure the repo renders well; please don’t change them or delete them and your repo will work fine :)