Python help recommend(user_id,network,similarity_matrix) This user_id will be us
ID: 3864504 • Letter: P
Question
Python help recommend(user_id,network,similarity_matrix) This user_id will be used as an index into the similarity_matrix which will give you access to the list of similarity scores for that given user (user_id) for all other users. You should then determine the largest value in this list and return its index as the most similar. Of course, you don’t want to recommend someone who is already a friend and it also doesn’t make sense to recommend the person as his or her own friend. It is the most similar because by having the largest value in the list it means that it is the user who had the most friends in common with user_id. (Hint: while developing this function using the small network file I printed out similarity_matrix[user_id] and network[user_id] so I could check that the correct recommendation was calculated.) def recommend(user_id,network,similarity_matrix): ''' Remember the docstring''' pass # this is a placeholder that you will replace with Python code
Explanation / Answer
After at least four years of tough criticism, it’s time to come to an intermediate conclusion about the state of NoSQL. So many things have happened around NoSQL that it is hard to get an overview and value what goals have been achieved and where NoSQL failed to deliver.
In many fields NoSQL has been more than successful in the industry and academics too. Universities are starting to understand that NoSQL must to be increasingly adopted by the curriculum. It is simply not enough to teach database normalization up and down. This, of course, does not mean that a profound relational foundation is wrong. To the contrary, NoSQL is certainly a perfect and important addition.
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