I have a dataframe with 3 columns and 1 label Here is an example of a row

key       | title               | description                                 | number
test-9999 | make sub projects   | a single projects can have its own projects | 5

description may have special characters like (/ , : ? =) and numbers.

title may just have special characters only.

key and number is fixed.

The problem I am facing now is I do not know which machine learning algo is best suited for my dataset and how to process the columns I have above.

  • $\begingroup$ Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. $\endgroup$
    – Community Bot
    Nov 26, 2021 at 13:34
  • $\begingroup$ Welcome to DataScienceSE. Special characters in the text don't really matter, they can be removed by preprocessing if needed. But you didn't say anything about your target task: what is the target class, how many instances, ...? $\endgroup$
    – Erwan
    Nov 26, 2021 at 16:59
  • $\begingroup$ Sorry for not clarifying in my post. The target is the number column between a range of 1 - 20. $\endgroup$
    – user128219
    Nov 27, 2021 at 2:50
  • $\begingroup$ @user128219 what does the number represent? Are the other columns good clues to predict the number, for example would somebody be able to guess the number based on the text in the other columns? If not ML is not going to help with this. $\endgroup$
    – Erwan
    Nov 27, 2021 at 16:22
  • $\begingroup$ the number represents the difficulty in completing the task from title description $\endgroup$
    – user128219
    Nov 28, 2021 at 2:03


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