Text classification with Convolution Neural Networks on Yelp, IMDB & sentence polarity dataset v1.0
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Updated
Sep 10, 2021 - Jupyter Notebook
Text classification with Convolution Neural Networks on Yelp, IMDB & sentence polarity dataset v1.0
Comparatively fine-tuning pretrained BERT models on downstream, text classification tasks with different architectural configurations in PyTorch.
This repository contains a DistilBERT model fine-tuned using the Hugging Face Transformers library on the IMDb movie review dataset. The model is trained for sentiment analysis, enabling the determination of sentiment polarity (positive or negative) within text reviews.
A Vagrant box that automatically loads the IMDB dataset into Postgres
🎬 An attempt at the most complete IMDb API
This repository contains analysis of IMDB data from multiple sources and analysis of movies/cast/box office revenues, movie brands and franchises.
Visualize the IMDB rating of every episode for any TV series.
Pytorch implementation of the paper Convolutional Neural Networks for Sentence Classification
Detect actor / actress faces in an image and list their work (movies / series)
In this implementation, using the Flan T5 large language model, we performed the Text Classification task on the IMDB dataset and obtained a very good accuracy of 93%.
🎥 R data package to explore Pixar films, the people, and reception data
Repository of state of the art text/documentation classification algorithms in Pytorch.
Topics related to Deep Learning
A machine learning model to recommend movies & tv series
Text Classification using Mamba Model
Fetch movie data from IMDB and output in JSON format.
Builds a Microsoft SQL Server 2016+ relational database from IMDb official data files, to support personal querying.
Transfer Learning model using RoBERTa on IMDb dataset deployed on React and Flask ( Regional Winner in Facebook Developer Community Challenge 2020 )
Sentiment analysis of IMDB dataset.
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