Tell us what’s happening:
I’ve adapted the solution for this exact problem from datascienceplus.com and I believe that my recommendations function is performing well but just doesn’t happen to yield all of the recommendations in the test. I’ve tried adjusting the K value as well as what data to use by filtering out books that do not meet a minimum rating count criteria but still I’m unable to pass the test. I’ve also tried stripping out all rows in the df_rating dataframe that had no ratings and that also did not work. Any suggestions on what I might be able to change to meet the requirements of this test would be appreciated. The one thing that I didn’t attempt to do at all from datascienceplus.com solution was to filter out users that were not from US or Canada but since the default workbook did not import the user data into a dataframe as it did with the other two files I assumed it was not needed for this project.
Your code so far
here is the link for my colab/jupyter notebook: https://colab.research.google.com/drive/1DihCAWUboS1K9-3UIeTLKgq_d4hK5tsm?usp=sharing
Your browser information:
User Agent is:
Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/84.0.4147.105 Safari/537.36.
Challenge: Book Recommendation Engine using KNN
Link to the challenge: