Deep Learning In Python - Week 4

An introduction to Python can be seen here:
Python for R users

Steps for Completing the Assignment

Step 1

Make a github account if you don't have one already.

Step 2:

Clone this github repository onto your laptop via a terminal, or use google colab, or kaggle...anywhere where you can edit python code. If your laptop doesn't work well, work on https://kaggle.com/. There are plenty of online resources which demo how to clone a repo e.g. here: https://www.earthdatascience.org/workshops/intro-version-control-git/basic-git-commands. (Notice that you need to install python if you decide to work on your laptop)

Step 3:

Edit the tasks.py file by filling in your solution code. Use the functions on test cases to see whether you have errors. You can also preview our test cases by running this command in the terminal

pip install pytest
pytest grade_task2.py

Notice that you shouldn't edit the grading files.

Step 4:

Add this week's kaggle notebook (there is no certificate) to the repository (https://www.kaggle.com/learn/nlp). This is not part of the grader but somewhat encouraged. It may be that no certificate is issued, in which case you can skip this part, but do submit the URL to your last notebook of this series on Canvas.

Step 5:

Push your changes to the repo back to github. The grading will occur automatically but might take a minute. Click the button Actions, atop the page, and select your latest commit, to see the Autograder outcomes. Again, the add/commit/push workflow of github is explained in various places online: https://www.earthdatascience.org/workshops/intro-version-control-git/basic-git-commands)