Libraries used:

import numpy as np
import pandas as pd
import csv
from sklearn.model_selection import train_test_split
import matplotlib.pyplot as plt
import seaborn as sns
from datetime import datetime
import os
from scipy import sparse
import time
from sklearn.metrics.pairwise import cosine_similarity
from surprise import Reader, Dataset
import random
import xgboost as xgb
from surprise import SVDpp
from surprise import SVD
from surprise import KNNBaseline
from surprise import SlopeOne
from surprise import CoClustering
from surprise import BaselineOnly

System Requirements:

-> Intel i7
-> 16 GB RAM
-> GTX 2060 RAM 6GB

How to run the code

All the dataset files could be downloaded from Kaggle dataset. Once the dataset is downloaded, the code has to be reconfigured and mapped to the files stored in the directory.

Time taken to run the project:

As the dataset is of size 2 GB, the whole execution of project may take greater than 20 hours to execute completely. The exact time taken to train and test ML models are shown in te code respectively.