Lab 7

• Ensure you have Jupyter.
  • Either install Jupyter alone or Anaconda.

• Familiarise yourself with Jupyter functionality. Consider taking LinkedIn Learning courses (free through the university) or any suitable alternatives. Here is a recommended set:

  • Introducing Jupyter
  • Get Ready for Your Coding Interview
  • Python for Data Visualization
  • Python: Programming Efficiently
  • Python Statistics Essential Training

• Load and study Investigating TSP.ipynb from GitHub.

  • See how large you can make n while testing exhaustive_search().
  • Check that greedy_nearest_neighbours() is correct. If not then fix it!

• You may try Google Colab and/or Microsoft Azure if that helps you work better, but please be aware that I am not sure about their GDPR compliance.

Todo

In advance of your lab session, you need to:

1. Refresh your knowledge of the key concepts covered in the lecture videos.
2. Attempt to solve the green exercises.
3. Then attempt the orange exercises.
4. Highlight any challenging exercises to ask about them during your lab sessions.
5. If you want to attempt the advanced/optional (red/blue) exercises then do so.