Content-Based Recommender Using Natural Language Processing (NLP)

Written by jnyh | Published 2020/08/11
Tech Story Tags: data-science | recommendation-systems | nlp | natural-language-processing | movies | content-recommendation | hackernoon-top-story | content-recommendation-brief | web-monetization

TLDR A guide to build a movie recommender model based on content-based NLP. Using Natural Language Processing (NLP) Using pandas as pd import numpy as np from sklearn.pairwise import cosine_similarity. The dataset is IMDB top 250 English movies downloaded from dataworld.com/jnyh. The data has to be pre-processed using NLP to obtain only one column that contains all the attributes (in words) of each movie. After that, this information is converted into numbers by vectorization, where scores are assigned to each word.via the TL;DR App
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Written by jnyh | perpetual student | fitness enthusiast | passionate explorer | https://github.com/jnyh
Published by HackerNoon on 2020/08/11
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