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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
This project offers advanced techniques in text preprocessing, word embeddings, and text classification. Explore methods like Word2Vec and GloVe, and master Multinomial Naive Bayes for accurate predictions. Dive into the world of text clustering and conquer challenges like unbalanced data.
This project is an NLP (Natural Language Processing) application that classifies BBC news articles into different genres, including sports, politics, entertainment, business, and technology. The classification is done using two different techniques: LSTM and GRU.
In this project, we'll generate our own Simpsons TV scripts using RNNs. We'll be using part of the Simpsons dataset of scripts from 27 seasons. The Neural Network we'll build will generate a new TV script for a scene at Moe's Tavern.