This repository is for Fake News Detection using Deep Learning models
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Updated
Feb 21, 2018 - HTML
This repository is for Fake News Detection using Deep Learning models
A model that predicts the sentiment for a given Amazon review. This is a Naive Bayes model that utilizes NLP for pre-processing.
VIP Machine Learning Exercises and Practices
( 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.
Implementation of Machine Learning Algorithms with Different Dataset
Repository aimed at building a simple recommender system for a content based dataset. The textual information is analysed so as to utilised as a more concrete piece of information!
Recommender system from Yelp dataset
This is a book analysis and recommendation system made in python and by using django framework, KNN, TF-IDF algorithm
Some NLP projects/assignments I've done in the past(Including beam search and tf-idf matrix from scratch)
Classification of books based on titles without prior knowledge of context or author
Movie recommender using movie reviews data from imdb
10 days 10 different practical applications of Deep Learning (primarily NLP) using Tensorflow and Keras
Compute the TF-IDF matrix from a collection of documents to measure the importance of words for text analysis and information retrieval tasks.
Parses apart a PDF file into separate documents and then uses Natural Language Processing, Machine Learning models, and statistics to rank the documents by similarity to a single document.
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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