Implement the Item-based collaborative filtering algorithm (please do not use any off the-shelf libraries for collaborative filtering, the idea is to implement the algorithm yourself)
• Step 1: Use the ratings specified in [login to view URL] file to learn similarity between movies. You can use the correlation coefficient (as given in the slides) or cosine similarity to compute the similarity weights.
• Step 2: For each row in [login to view URL], predict the rating based on a neighborhood of similar movies. Refer to the slides on collaborative filtering for the equation used to compute the predicted rating. You can select any appropriate neighborhood size when making the prediction.
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Hi there, I am a software developer, with a diploma in Data Science (Data Analytics). I am familiar with Python and Machine Learning, I believe I am able to help you out. Looking forward to hearing from you!