/P35.-Unsupervised-ML---Recommendation-System-Data-Mining-Movies-

Unsupervised-ML-Recommendation-System-Data-Mining-Movies. Recommend movies based on the ratings: Sort by User IDs, number of unique users in the dataset, number of unique movies in the dataset, Impute those NaNs with 0 values, Calculating Cosine Similarity between Users on array data, Store the results in a dataframe format, Set the index and column names to user ids, Slicing first 5 rows and first 5 columns, Nullifying diagonal values, Most Similar Users, extract the movies which userId 6 & 168 have watched.

Primary LanguageJupyter Notebook

P35.-Unsupervised-ML---Recommendation-System-Data-Mining-Movies-

Recommend movies based on the ratings:

Sort by User IDs

number of unique users in the dataset

number of unique movies in the dataset

converting long data into wide data using pivot

Replacing the index values by unique user Ids

Impute those NaNs with 0 values

Calculating Cosine Similarity between Users on array data

Store the results in a dataframe format

Set the index and column names to user ids

Slicing first 5 rows and first 5 columns

Nullifying diagonal values

Most Similar Users

extract the movies which userId 6 & 168 have watched