Technology Review of GloVe word vector generation model
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Updated
Nov 5, 2021
Technology Review of GloVe word vector generation model
A 2-layer Bidirectional LSTM based model to classify a Quora question as insincere or not. This was my project in "ECE 542: Neural Networks and Deep Learning" course at NC State University.
Sentiment analysis on IMDB dataset using GloVe pre-trained embeddings and LSTM.
NLP task for classification of comments into their emotional meaning
Text classification algorithm used to identify tweets regarding disasters
Generate captions for images, describing it
Improving Topic Models with Word Embeddings
Being anonymous over the internet can sometimes make people say nasty things that they normally would not in real life. Let's filter out the hate from our platforms one comment at a time.
Some useful examples of Deep Learning (.py)
This is a novel Transformer network based approach to distinguish ChatGPT generated Text from Human text. The model was also deployed on local server using Flask where Docker was used to manage all dependencies.
Data and code for the machine learning exam assignment of MA Digital Text Analysis (2023).
using AI to answer the Analogy question
Predicts the suitable emoji when a sentence given.
Detecting Sarcasm using BiDirectional LSTM and GloVe embeddings
Text classification problem using Bidirectional Recurrent Neural Network (BRNN) with glove 6B_50d word embedding
Wikipedia Scraper & AI Topic Classifier written in React.JS and Python.
This notebooks, we train a seq2seq decoder model with teacher forcing. Then use the trained layers from the decoder to generate a sentence.
Optimize WordNet exploration with a semantic search algorithm, utilizing GloVe embeddings and CNF logic. Efficiently pinpoint target synsets within a constrained step count. Investigate parallel processing and optimization for enhanced performance. #WordNet #GloVe #SemanticSearch #CNF #Optimization #NLP
Use Reddit News Headlines to predict the movement of Dow Jones Industrial Average.
Add a description, image, and links to the glove-embeddings topic page so that developers can more easily learn about it.
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