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Spanish word embeddings computed with different methods and from different corpora
Extracting Skills from resume using Machine Learning
The backed for an anime recommender system that combines multiple methods to provide a variety of recommendations to users based on different similarity metrics
Information retrieval course project
create the search engine to retrieve the text documents. (the information retrieval course project)
Sentiment Analysis on Loksabha Elections 2019
Text classification is the task of assigning a set of predefined categories to free text. Text classifiers can be used to organize, structure, and categorize pretty much anything. For example, new articles can be organized by topics, support tickets can be organized by urgency, chat conversations can be organized by language, brand mentions can be organized by sentiment, and so on.
M.Sc. mini project for NLP class (M908)
Bengali word embedding using BengaliWord2Vec from BNLP. A mini project under the mentorship of Prof. Sandipan Ganguly, HIT-K.
Automatic library of congress classification, using word embeddings from book titles and synopses.
Checkout my adventures into NLP here.
This is final project of Information Retrieval course which is implementation of a search engine
An Empirical Evaluation of Word Embedding Models for Subjectivity Analysis Tasks
Arabic Word Embedding models SkipGram, and GLoVE are trained over Arabic Wiki data Dump 2018 dataset from scratch using Gensim and GLoVE python libraries. Then the models are evaluated on three NLP tasks and its results are visualized in T-SNE
🎬 Analyze movie reviews sentiment in real-time with "Sentiment Analysis on Movie Reviews using Word2Vec"! Powered by advanced NLP and deployed using Streamlit, this app categorizes reviews as positive or negative. Perfect for film enthusiasts and industry professionals! 🍿📊
Sentiment analysis is the process of detecting positive or negative sentiment in text. It’s often used by businesses to detect sentiment in social data, gauge brand reputation, and understand customers.
The project focuses on developing medical word embeddings using Word2vec and FastText in Python to create a search engine and Streamlit UI. The use of embeddings helps overcome the challenges of extracting context from text data, making it easier to represent words as semantically meaningful dense vectors.
[FR - Duo] 2023 - 2024 Centrale Méditerranée AI Master | NLP project about embeddings and word2vec algorithm
Example of how to use word embedding with BlazingText algorithm in Amazon SageMaker on entire contents of wikipedia for a foreign language (Hebrew).
NLP demos and talks made with Jupyter Notebook and reveal.js
In this project we will be building a text classifier using LSTM and Wor2vec
Patent Big Data Analysis Platform for Individual Patent Applicants
Experiments in the field of Semantic Search using BM-25 Algorithm, Mean of Word Vectors, along with state of the art Transformer based models namely USE and SBERT.
The project aimed to classify Gutenberg texts accurately. Employing advanced NLP methodologies, it covered collection, preprocessing, feature engineering, and model evaluation for literary work classification. as part of the University of Ottawa's 2023 NLP course.
Comparison of contextual (BERT) and uncontextual (GloVe and Word2Vec) word embeddings in the task of music genre classification from lyrics.
HateXplain AAAI 2021 Reproducibility Challange
Arabic part of speech tagging using arabic PUD dataset using bidirectioanl LSTM for sequential labeling classification
Emotion Analysis with Transformers
Projects of Machine learning and Deep learning
A tool to assess semantic similarity between English words
This project implements a Word2Vec model for similar word prediction, utilizing Hugging Face Datasets for efficient data loading and pre-processing.
Hindi-Text-summarization-major project