Machine Learning Tutorial Part 6 | Knn(Friend Recommender) For Beginners

Machine Learning tutorial | Python K Nearest Neighbor(KNN) | Artificial Intelligence | Unsupervised learning, Supervised Learning and Reinforcement Learning | Recommender system

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K Nearest Neighbor(KNN) is a very simple, easy to understand, versatile and one of the topmost machine learning algorithms. KNN used in the variety of applications such as finance, healthcare, political science, handwriting detection, image recognition and video recognition. In this video we will implement it in a Friend Recommender Application.

Interested in machine learning or do you just want to make a recommender system on your own? Then this course is all you need! You will learn how to crawl data(data mining), setup a database for storing data and then use this data to recommend items to the users within your system.

For full course: https://www.udemy.com/python-data-mining-and-machine-learning/?couponCode=VINSLOEV

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For more info about Surprise Framework see:
http://surpriselib.com/

Dataset used in the video:
movies = ['Star wars', 'Star wars', 'GOT', 'GOT', 'South Park', 'South Park', "Harry potter", "Harry potter"]
rating = [1, 5, 1, 1, 5, 3, 2, 5]
users = ['Kim', 'Tim', 'John', 'Jimmy', 'Julia', 'Kim', 'Jimmy', 'Kim']