Text Classification of Legitimate and Rogue Online Privacy Policies: A manual analysis and an experimental procedure
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Updated
Apr 20, 2017 - Java
Text Classification of Legitimate and Rogue Online Privacy Policies: A manual analysis and an experimental procedure
A content based movie recommender system.
IMDB movie review classification using neural network (text-vectorization v/s word-embeddings)
Evaluation of the accuracy of vectorization and text classification methods
Homeworks and final project for Infosearch course
This is a Content-based Movie Recommendation App wherein the user can type in a particular movie that he/she has enjoyed and can get the names and posters of top 5 similar movies.
Discussion about Probabilities, Classification and Zipf's law
Movie Recommender System leverages a content-based approach, suggesting films to users based on the attributes of movies they have previously enjoyed. By analyzing movie metadata such as genre, cast, director, keywords, etc., this project offers personalized recommendations aligned with users' cinematic tastes.
Tag prediction on Stack Overflow using TensorFlow Keras and Text Vectorization
Experiments in the field of Sentiment Analysis using ML Algorithms namely Logistic Regression, Naive Bayes along with tfidf, one hot encoding, bag of words vectorization. Different MLP and RNN models viz. LSTM, GRU, Bidirectional LSTM. Lastly, state of the art BERT model
The repository contains notebooks created for collecting and preprocessing the corpus of diary entries and for experiments on creating models for predicting gender, age groups of authors and the time period of text creation.
Naive Bayes classifier with text parser and vectorization libs
A dynamic Movie Recommender web app using ML text vectorization technique to suggest the user with similar kind of movies and their posters.
This project is an unsupervised NLP-based recipe recommender system designed to provide personalized recipe suggestions. The system employs content-based filtering techniques, utilizing cosine similarity to measure the resemblance between user inputs and a database of recipes.
Machine Learning course of Piero Savastano 3: CountVectorizer
Data science and NLP tools developed for my own use.
Successfully established a machine learning model that can accurately classify an e-commerce product into one of four categories, namely "Books", "Clothing & Accessories", "Household" and "Electronics", based on the product's description.
Content Based Movie Recommendation System | Python
Sentiment Analysis
Performing sentiment analysis on movie reviews using RNN (LSTM) in keras
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