Comparatively fine-tuning pretrained BERT models on downstream, text classification tasks with different architectural configurations in PyTorch.

Text classification with Convolution Neural Networks on Yelp, IMDB & sentence polarity dataset v1.0

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.

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

Pytorch implementation of the paper Convolutional Neural Networks for Sentence Classification

Detect actor / actress faces in an image and list their work (movies / series)

Text Classification using Mamba Model

Nano-BERT is a straightforward, lightweight and comprehensible custom implementation of BERT, inspired by the foundational "Attention is All You Need" paper. The primary objective of this project is to distill the essence of transformers by simplifying the complexities and unnecessary details.

Topics related to Deep Learning

A machine learning model to recommend movies & tv series

Sentiment analysis of IMDB dataset.

Repository of state of the art text/documentation classification algorithms in Pytorch.

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.