GitHub topics: tfidf-matrix
bluntjudg/Book-Recommendation-System-
This project uses machine learning to create a personalized bookrecommendation system. By combining collaborative filtering and content-based filtering, it analyzes user preferences and book attributes to suggest tailored book recommendations. The system offers real-time updates and accurate predictions to enhance the user experience.
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akshaybhatia10/Book-Genre-Classification
Classification of books based on titles without prior knowledge of context or author
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VipinJain1/VIP-Machine-Learning-Exercises-and-Practices
VIP Machine Learning Exercises and Practices
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mustaffa-hussain/TFIDF-Vectorization
( Scratch development ) Term Frequency Inverse Document Frequency is a vectorization technique used widely in Natural Language Processing. The vectorization effectively gives importance to rare words and important words.
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harsh306/fake_news_detection_deep_learning Fork of nguyenvo09/fake_news_detection_deep_learning
This repository is for Fake News Detection using Deep Learning models
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Vaibhavs10/10_days_of_deep_learning
10 days 10 different practical applications of Deep Learning (primarily NLP) using Tensorflow and Keras
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mo-inkhan/TF-IDF-Vectorizer
Compute the TF-IDF matrix from a collection of documents to measure the importance of words for text analysis and information retrieval tasks.
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peterzee-tsien/NLP_projects
Some NLP projects/assignments I've done in the past(Including beam search and tf-idf matrix from scratch)
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yashbrid03/BOOKFLIX-Analysis-and-Recommendation-System-
This is a book analysis and recommendation system made in python and by using django framework, KNN, TF-IDF algorithm
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bhaskars9/movie-recommender
Movie recommender using movie reviews data from imdb
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Mayurji/Machine-Learning
Implementation of Machine Learning Algorithms with Different Dataset
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