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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%.
This is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets. We provide a set of 25,000 highly polar movie reviews for training and 25,000 for testing.
This repository contains a project that involves creating and managing a MySQL database using the IMDb dataset. It includes scripts and instructions for setting up the database, importing the IMDb dataset, and performing various queries to extract meaningful insights from the data.
IMDb JSON Datasets. Subsets of IMDb data are available for access to customers for personal and non-commercial use. You can hold local copies of this data, and it is subject to our terms and conditions. Please refer to the Non-Commercial Licensing and copyright/license and verify compliance.
A repository for the source code, notebooks, data, files, and other assets used in the data science and machine learning articles on LearnDataSci - articles/Python Pandas Tutorial A Complete Introduction for Beginners/IMDB-Movie-Data.csv at master · LearnDataSci/articles
Python package to both parse datsets provided by IMDb and scrape information from imdb.com
Introduction: This GitHub repository contains the code and documentation for an exploratory data analysis (EDA) project on the IMDb dataset. The IMDb dataset is a rich source of information about various movies, including details like titles, genres, ratings, revenues, and more.
A Python-based movie data analyzer that explores the top 10 most popular movies from an IMDb dataset. It provides various visualizations, including correlations between budget and revenue, genre distributions, and more, with detailed statistics to gain insights into movie trends.
Aug 23, 2022 · This project aims to analyze the provided IMDB movie dataset to uncover factors influencing movie success. Beginning with data cleaning and manipulation to handle missing values, duplicates, and feature engineering if necessary, the analysis progresses through various tasks.
Sentiment analysis Convolutional Neural Network with Keras Functional API on IMDb dataset using GloVe pretrained word embeddings
