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dl-s2-2022-cw2's Introduction

Introductory Applied Machine Learning (IAML) Coursework 2 - Semester 2, 2021/22.

Author: Hiroshi Shimodaira and Shuzhuang Xu

Important Instructions

It is important that you follow the instructions below carefully for things to work properly.

You need to set up and activate your environment as you would do for your labs, see Learn section on Labs. In brief:

  1. Log into the Noteable and start or reconnect to a Standard Notebook.
  2. Cick on the "+GitRepo" button, then copy this link, https://github.com/uoe-iaml/DL-S2-2022-CW2, to the "Git Repository URL" box in the dialog.
  3. Replace "master" with "main" in the "branch" box in the dialog.
  4. Click on "clone" to import all the lab materials to your Noteable space.
  5. Click on IAML-21-22-S2-DL-CW2.ipynb to start up the assignment Notebook. It is important that you follow the instructions below carefully for things to work properly.

You will need to use Noteable to create one of the files you will submit (the PDF). Do NOT create the PDF in some other way, we will not be able to mark it. If you want to develop your answers in your own environment, you should make sure you are using the same packages we are using, by running the cell which does imports below.

Read the instructions in this notebook carefully, especially where asked to name variables with a specific name. Wherever you are required to produce code you should use code cells, otherwise you should use markdown cells to report results and explain answers. In most cases we indicate the nature of answer we are expecting (code/text), and also provide the required code/markdown cell.

  • We will use the IAML Learn page for any announcements, updates, and FAQs on this assignment. Please visit the page frequently to find the latest information.

  • Data files that you will be using are included in the git repository for this coursework.

  • There is a helper file 'iaml22cw2_helpers.py' which you should upload to your environment.

  • Some of the topics in this coursework are covered in week 8 of the course. Focus first on questions on topics that you have covered already, and come back to the other questions as the lectures progress.

  • Keep your answers brief and concise.

  • Make sure to show all your code/working.

  • Write readable code. While we do not expect you to follow PEP8 to the letter, the code should be adequately understandable, with plots/visualisations correctly labelled. Do use inline comments when doing something non-standard. When asked to present numerical values, make sure to represent real numbers in the appropriate precision to exemplify your answer.

  • When you use libraries specified in this coursework, you should use the default parameters unless specified explicitly.

  • The criteria on which you will be judged include the quality of the textual answers and/or any plots asked for.

  • You will see \pagebreak at the start of each subquestion. Do not remove these, if you do we will not be able to mark your coursework.

Good Scholarly Practice

Please remember the University requirement regarding all assessed work for credit. Details about this can be found at: http://web.inf.ed.ac.uk/infweb/admin/policies/academic-misconduct Specifically, this assignment should be your own individual work. We will employ tools for detecting misconduct.

Moreover, please note that Piazza is NOT a forum for discussing the solutions of the assignment. You may ask private questions. You can use the office hours to ask questions.

SUBMISSION Mechanics

This assignment will account for 30% of your final mark. We ask you to submit answers to all questions.

You will submit (1) a PDF of your Notebook via Gradescope, and (2) the Notebook itself via Learn. Your grade will be based on the PDF, we will only use the Notebook if we need to see details. You must use the following procedure to create the materials to submit.

  1. Make sure your Notebook and the datasets are in Noteable and will run. If you developed your answers in Noteable, this is already done.

  2. Select Kernel->Restart & Run All to create a clean copy of your submission, this will run the cells in order from top to bottom. This may take a while (a few hours) to complete, ensure that all the output and plots have complete before you proceed.

  3. Select File->Download as->PDF via LaTeX (.pdf) and wait for the PDF to be created and downloaded.

  4. Select File->Download as->Notebook (.ipynb)

  5. You now should have in your download folder the pdf and the notebook. Rename them sNNNNNNN.pdf and sNNNNNNN.ipynb, where sNNNNNNN is your matriculation number (student number).

Details on submission instructions will be announced and documented on Learn well before the deadline.

The submission deadline for this assignment is 5th April 2022 at 16:00 UK time (UTC). Don't leave it to the last minute!

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