Write your Data analysis and reports.https://www.kaggle.com/ruchi798/bookcrossing-datasetPlease use the above dataset for a recommendation system project. We want to recommend books to a user if we enter their user id based on their data. I would like to have different models used for classification with varying weightages to the book ratings, demographics, or any other combination of attributes. Please include a comparative study of the different models built – SVM, KNN and Naive Bayes atleast.Please explain the steps in detail for each case in the console.I would like to see metrics- precision, recall and f1-score for each model built for comparison.Further optimization on the model parameters should also be done in order to better the results.Whatever is done, each step from start to finish- including the starting model and the changes made over time to reach the best model- should be included.
