Submission¶
THA 7 - Tweet Topic Modelling
You may submit any part of the assignment as many times as you want before the late cutoff (remember submitting after the due date will cost late days).
For each homework assignment, there will usually be two things to submit:
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A Conceptual portion that asks you to solve conceptual questions about that week’s materials. This part counts towards the Concept Portion of your assignment grade. You will turn in Concept portions on Gradescope.
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A Programming portion that asks you to answer questions or do an analysis involving programming. This counts towards your Programming portion of your final grade. You will turn in Programming portions on Ed
Please make sure you are familiar with the late day policy and collaboration policy on the syllabus.
Conceptual¶
Submit the conceptual questions directly on Gradescope. You can submit your answers as many times as you want before the late cutoff (submitting after the due date will cost late days). Conceptual questions are graded manually and feedback will be posted after a period for the course staff to grade.
Programming¶
Complete and submit the Jupyter notebook of the programming assignment here by pressing the Mark button:
This and other Programming portions will be using EdStem as your tool to edit your solutions. We will use a programming format known as a “Jupyter Notebook” this quarter, as they are a common tool amongst data scientists to develop and communicate their results. EdStem supports hosting and running of Jupyter Notebooks, as well as providing us means for autograding them.
When you first visit the assignment, you will get a copy of the starter code (called a “Scaffold”). You will then be freely able to edit your starter code with whatever work you want. You can always reset your code back to the Scaffold by clicking the “…” on the top-right and then “Reset to Scaffold”. But be careful! That will erase all of your current work.
Every time you press “Mark” you will make a submission of your assignment that will be run against the staff autograder. This autograder will run your code on a modified version of the dataset to ensure its correctness. The autograder is there to help you feel confident about the behavior of your solution, but we will still manually grade the programming assignments to make sure your solution meets the stated specification.