Comparatively fine-tuning pretrained BERT models on downstream, text classification tasks with different architectural configurations in PyTorch.
Project 0 for the Introduction to "Artificial Intelligence with Python" Harvard online course. App that finds a connection between two actors bases on the movies they have starred in, using BFS algorithm.
Bunch of examples of a "Simple but tough to beat baseline for sentence embeddings" in classification tasks
Text Classification using Mamba Model
Detect actor / actress faces in an image and list their work (movies / series)
IMDB's website full scraping of title, rating, actors, genres and more which produces a csv file (using an API too). Including cleaning and a machine learning algorithm that predict the IMDB rating based on differents criterias.
Pytorch implementation of the paper Convolutional Neural Networks for Sentence Classification
Sentiment of a movie review is predicted using three different neural network models - MLP, CNN and LSTM. GloVe embedding is used for vector representation of words.
Sentiment classification and opinion prediction based on a movie reviews dataset.
An Artificial Intelligence (AI) project for course CS5100 at Northeastern University
sentiment analysis of textual documents (reviews, twitters) using different learning architectures (doc2vec, LSTM)
Movie Counsel helps you to get tailored Movie/Series recommendation with an inbuilt Sentiment Analyzer Tool for Movie Reviews
A machine learning model to recommend movies & tv series
Movie information extraction from TMDB API.
NLP sample project leveraging modelkit and the imdb reviews dataset
This project aims to classify Imdb reviews according to their sentiments by using a Bidirectional LSTM model.
A command line IMDb search application that can also download movie posters.
This project contains a dataset comprising of information about Hollywood movies released between 1990 and 2019 and it was collected using a polite webscraper. Please keep in mind that IMDB doesn't permit the usage of its data for commercial purposes and this project was solely made for educational purpose.
Makes a folder with separated sorted symbolic links from a messy large download folder without moving the files (symbolic links is awesome)
Add a description, image, and links to the imdb-dataset topic page so that developers can more easily learn about it.
To associate your repository with the imdb-dataset topic, visit your repo's landing page and select "manage topics."