Ex-5: Multiclass Classifier

Overview

In this exercise, you will implement a multiclass classifier using the concepts learned in previous exercises.

Objectives

1. Enhance your understanding of multiclass classification.
2. Reuse and modify solutions from previous exercises.
3. Implement and train a multiclass classifier model.
4. Evaluate the performance of the model.

The Assignment

You can reuse your solutions for define_dense_model_single_layer and define_dense_model_with_hidden_layer from Exercise 4. However, you need to fill in the functions fit_mnist_model and evaluate_mnist_model. Try to experiment with the number of epochs and batch size if the tests do not pass initially.

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Validating and Evaluating Your Results

Online

1. After committing and pushing your code, check the mark on the top line (near the commit ID).
2. If some tests are failing, click on the ❌ to open up a popup, which will show details about the errors.
3. You can click the Details link to see what went wrong. Pay special attention to lines with the words "Failed" or "error".

4. Near the bottom of the Details page, you can see your score. Here are examples of 0/5 and 5/5:

5. When you achieve a perfect score, you will see a green checkmark near the commit ID.

Locally

1. You can test your code locally by installing and running pytest (pip install pytest or conda install pytest).
2. Run the tests using the command pytest in your terminal. This will show the status of each test and any errors that occurred.

Good luck!