Notebook: MLP Classification

Now, you're ready to define and train an MLP in PyTorch. As you follow along this lesson, you are encouraged to open the referenced Jupyter notebooks. We will present a solution to you, but please try creating your own deep learning models! Much of the value in this experience will come from experimenting with the code, in your own way.

To open this notebook, you have two options:

• Go to the next page in the classroom (recommended).
• Clone the repo from Github and open the notebook mnist_mlp_exercise.ipynb in the convolutional-neural-networks > mnist-mlp folder. You can either download the repository with git clone https://github.com/udacity/deep-learning-v2-pytorch.git , or download it as an archive file from this link .

Instructions

• Define an MLP model for classifying MNIST images
• Train it for some number of epochs and test your model to see how well it generalizes and measure its accuracy.

This is a self-assessed lab. If you need any help or want to check your answers, feel free to check out the solutions notebook in the same folder, or by clicking here .