word-embeddings

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Here are 32 public repositories matching this topic...

Fran-Benko / reviewer-app

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A simple web app that uses a trained sequential neural net to predict the rating of a hotel review.

nlp deep-learning neural-network word-embeddings principal-component-analysis tf-idf-vectorizer

Updated Feb 10, 2021
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abhijit57 / Intent-Classification-and-Sequence-Labelling

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Intent classification is the automatic categorization of text data based on customer goals. It is known to be a complex problem in NLP. Sequence Labelling aims to classify each token (word) in a class space C. This project addresses these two problem statements by covering the basic concepts of NLP to advanced ones. For instance, linguistics ana…

nlp machine-learning deep-learning word-embeddings transformers n-grams bag-of-words transfer-learning tfidf bert count-vectorizer intent-classification sequence-labelling bio-tagging

Updated Jul 17, 2022
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BKHMSI / Word-Walk

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angularjs word2vec word-embeddings web-application embeddings nlp-machine-learning linear-interpolation embeddings-word2vec

Updated May 10, 2019
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arif-cakir / GraduationProject

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Spring 2023 graduation thesis for mathematical engineering program of Istanbul Technical University

natural-language-processing word2vec word-embeddings

Updated Jan 30, 2024
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sweta-kesur-nlp-playground / nlp-play1-movie-reviews

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Real time application of Sentiment Analysis on Movie Reviews. A Machine Learning Flask App hosted on Heroku and created on Google Colab. https://swetakesurnlp-playground.herokuapp.com

heroku nlp flask natural-language-processing tutorial sentiment-analysis naive-bayes word-embeddings cnn lstm heroku-deployment lstm-sentiment-analysis google-colab reccurent-neural-network

Updated Jan 12, 2022
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antonio-f / DeepLearning_Project3-TV-script-generation

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Generate a TV script using RNNs

tensorflow word-embeddings text-generation recurrent-neural-networks rnn udacity-deep-learning script-generator

Updated Dec 25, 2017
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gederajeg / vector_space_model_indonesian

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Repository for R Markdown Notebook containing codes for the paper "vector space models and the usage patterns of Indonesian denominal verbs" (published in NUSA)

word2vec word-embeddings vector-space-model corpus-linguistics indonesian-language r-programming indonesian r-notebook r-project leipzig-corpora-collection indonesian-morphology

Updated Apr 1, 2020
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damounayman / Text-Mining-and-Chatbots

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nlp chatbot word-embeddings named-entity-recognition

Updated Feb 20, 2021
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xiangyutang2 / image-captioning

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Image Captioning using Neural Networks

machine-learning neural-network word-embeddings cnn rnn image-captioning transfer-learning vgg16 fusion-model

Updated Jun 20, 2019
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RUI2190 / Multi-linguistic-Topological-Analysis

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DSC 214 Topological Data Science Project

multilingual word-embeddings topology-visualiztion topological-data-analysis

Updated Jun 28, 2024
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rimonim / ds4psych

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Data Science for Psychology: Natural Language

data-science social-media r dataviz deep-learning sentiment-analysis text-classification word-embeddings tidyverse psychology rstats apis quarto natural-language-procressing

Updated Dec 22, 2024
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eyabesbes / Orange-learning-Program

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This repository houses projects completed as part of the Google Career Certificates program offered through the Orange Learning initiative, sponsored by Orange Digital Center, Google, and Coursera.

deep-learning time-series word-embeddings data-visualization gan

Updated May 1, 2025
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SAMY-ER / Text-Classification-Methods

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This repository is an effort to showcase different text classification approaches on a consumer complaints dataset.

python machine-learning text-classification clustering word2vec word-embeddings neural-networks language-models bert

Updated Oct 15, 2019
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miguelangelnieto / TV-Script-Generation

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Generated own Simpsons TV scripts using RNNs.

tensorflow word-embeddings recurrent-neural-networks preprocessing

Updated Feb 7, 2018
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SalmaYehia1 / Word-Embeddings.github.io

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This web page explains how words are transformed into numerical vectors, or embeddings, enabling AI models to process human language. It covers the evolution of embedding techniques, from basic frequency-based methods to modern context-aware models like BERT.

nlp word-embeddings