imdb-dataset
There are 4 repositories under imdb-dataset topic.
cmasch / cnn-text-classification
Text classification with Convolution Neural Networks on Yelp, IMDB & sentence polarity dataset v1.0
Language:Jupyter Notebook 116uzaymacar / comparatively-finetuning-bert
Comparatively fine-tuning pretrained BERT models on downstream, text classification tasks with different architectural configurations in PyTorch.
Language:Python 115RyanMarcus / imdb_pg_dataset
A Vagrant box that automatically loads the IMDB dataset into Postgres
Language:Shell 56zyh040521 / distilbert-base-uncased-finetuning
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.
Language:Jupyter Notebook 49kunalnagarco / imdb-scraper
š¬ An attempt at the most complete IMDb API
Language:TypeScript 34mansik95 / IMDB-Analysis
This repository contains analysis of IMDB data from multiple sources and analysis of movies/cast/box office revenues, movie brands and franchises.
Language:TSQL 27madnight / imdb-series-chart
Visualize the IMDB rating of every episode for any TV series.
Language:JavaScript 24leohsuofnthu / Pytorch-TextCNN
Pytorch implementation of the paper Convolutional Neural Networks for Sentence Classification
Language:Python 20RafaelMenesesRibeiro / FaceRecognition
Detect actor / actress faces in an image and list their work (movies / series)
Language:Python 18M-Taghizadeh / flan-t5-base-imdb-text-classification
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%.
Language:Jupyter Notebook 17- pixarfilms
erictleung / pixarfilms
:movie_camera: R data package to explore Pixar films, the people, and reception data
Language:R 16 gaurav104 / TextClassification
Repository of state of the art text/documentation classification algorithms in Pytorch.
Language:Jupyter Notebook 11surfertas / deep_learning
Topics related to Deep Learning
Language:Jupyter Notebook 11Prajwal10031999 / Movie-Recommendation-System-Using-Cosine-Similarity
A machine learning model to recommend movies & tv series
Language:Python 10pushshift / imdb_to_json
Fetch movie data from IMDB and output in JSON format.
Language:Python 9sleepingdog / IMdb-sql-queries
Builds a Microsoft SQL Server 2016+ relational database from IMDb official data files, to support personal querying.
Language:TSQL 9- Imdb-movie-review-analysis-using-NLPLanguage:Jupyter Notebook 8
mohdahmad242 / Transfer-Learning-Model-hosted-on-Heroku-using-React-Flask
Transfer Learning model using RoBERTa on IMDb dataset deployed on React and Flask ( Regional Winner in Facebook Developer Community Challenge 2020 )
Language:Jupyter Notebook 8advaitsave / Text-preprocessing-and-classification
IMDB Movie Reviews - Text preprocessing and classification. Includes BOW model, TF_IDF, VADER entiment analysis, Topic Modelling using Latent Dirichlet Allocation and Word Embeddings. (Python)
Language:Jupyter Notebook 7StepanTita / nano-BERT
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.
Language:Jupyter Notebook 7tareqmahmud / IMDBScraping
Scrape Data From IMDB Movie DataBase
Language:Python 7manaswikamila05 / RSVP-Movies
SQL queries performed on IMDb database to provide recommendations to RSVP Movies based on insights.
Language:SQL 6zembrodt / pymdb
Python package to both parse datsets provided by IMDb and scrape information from imdb.com
Language:Python 6abhishekde94 / rsvp_movies
RSVP Movies is an Indian film production company which has produced many super-hit movies. They have usually released movies for the Indian audience but for their next project, they are planning to release a movie for the global audience in 2022.
Ankit152 / IMDB-sentiment-analysis
Sentiment analysis of IMDB dataset.
Language:Jupyter Notebook 5blurred-machine / IMDB-Movies-Reviews-Classification-NLP
Research oriented, developing word embeddings for binary text-polarity classifier based on movie reviews using BoW, TF-IDF, n-Gram, Word2Vec, Doc2Vec, PV-DM, PV-DBOW and other NLP techniques.
Language:Jupyter Notebook 5omerfarukeker / imdb_work
Exploratory analysis on the IMDB movie database
Language:Python 5- Language:Elixir 5
prakruti-joshi / Gated-Attention-Network
PyTorch implementation of the Gated Attention Network for text classification. Comparison of the model with BiLSTM and soft attention models using IMDb and TREC dataset.
Language:Jupyter Notebook 5santanukumar666 / Movie-Genre-Detection-From-Posters
This project aims at determinig the genre of the movie using its posters for image classifications CNNs are the most effective types of neural network in this project we try to create a CNN which would predict the genres of these movies.
Language:HTML 5SOUMEE2000 / Machine-Learning-Stash
Some of my projects and notebooks related to Machine Learningš in one place and not scattered all over GitHub. Check out the README.md in the respective folders first.
Language:Jupyter Notebook 5talmago / simple-but-tough-to-beat-examples
Bunch of examples of a "Simple but tough to beat baseline for sentence embeddings" in classification tasks
Language:Python 5- Language:SQL 5
zhiming-xu / spoiler-detector
Detect spoilers in IMDb movie reviews with deep neural network
Language:Jupyter Notebook 5course-dprep / MovieGenre_IMDbAnalysis
This repository aims to shed a light on the effect of movie genre on its IMDb popularity score.
Language:R 4thakurdiwakar / Movie-Recommendation-System
This Movie Recommendation System is a Python-based application that leverages machine learning and natural language processing techniques to provide movie recommendations based on user preferences and movie characteristics.
Language:Jupyter Notebook 4
