A Python toolbox for gaining geometric insights into high-dimensional data
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Updated
Mar 19, 2024 - Python
A Python toolbox for gaining geometric insights into high-dimensional data
The project has text vectorization, handling big data with merging and cleaning the text and getting the required columns while boosting the performance by feature extraction and parameter tuning for NN, compares the Performances through applied different models treating the problem as classification and regression both.
📖 Use Bi-normal Separation to find document vectors which is used to compute similarity for shorter sentences.
Comment Sentiment Analysis using Deep Learning
Word Factor Vectors
Given a document, identifying the closest documents within the list of documents using tf-idf matrix and cosine similarity
A simple Python script for transforming a corpus of documents into text vectors suitable for visualization
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
Text Classification of Legitimate and Rogue Online Privacy Policies: A manual analysis and an experimental procedure
Syracuse University, Masters of Applied Data Science - IST 736 Text Mining
Evaluation of the accuracy of vectorization and text classification methods
Using text-vectorization and similarity-based-matrix computation
IMDB movie review classification using neural network (text-vectorization v/s word-embeddings)
A content based movie recommender system.
Predictive Text Analysis project! This repository contains code for predicting answers to science exam questions using advanced natural language processing techniques. Check out the code and results!
Homeworks and final project for Infosearch course
In this notebook we analyze and classify news articles using machine learning techniques, including Logistic Regression, Naive Bayes, Support Vector Machines, and Random Forests. Explore text vectorization and NLP for accurate news categorization.
A diploma project focused on vectorizing scientific texts using the Top2Vec algorithm, with the aim of analyzing thematic groups, identifying trends, and visualizing the dynamics of interest in various topics in the field of computer science.
Clustering text using text vectorization
demistifying nlp with a series of nlp implementation notebooks.
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