finding nearest neighbors if we want to build recommender systems such as movie recommender system then we need to understand the concept of finding the nearest neighbors it is because the recommender system utilizes the concept of nearest neighbors the concept of finding nearest neighbors may be defined as the process of finding the closest point to the input point from the given dataset the main use of this knn) -nearest neighborsalgorithm is to build classification systems that classify data point on the proximity of the input data point to various classes the python code given below helps in finding the -nearest neighbors of given data setimport the necessary packages as shown below nearestneighbors module from the sklearn packageherewe are using the import numpy as np import matplotlib pyplot as plt from sklearn neighbors import nearestneighbors let us now define the input dataa np array([[ ][ ][ ][ ][ ],[ ][ ][ ][ ][ ],]nowwe need to define the nearest neighborsk we also need to give the test data from which the nearest neighbors is to be foundtest_data [ the following code can visualize and plot the input data defined by usplt figure(plt title('input data'plt scatter( [:, ] [:, ]marker=' ' = color='black'