Real-time face detection and emotion/gender classification using fer2013/imdb datasets with a keras CNN model and openCV.

A new large-scale noise-controlled face recognition dataset.

A celebrity face recognition service built with Serverless Framework using Twilio, Amazon Rekognition, Boto3 and IMDB API.

Detect face and gender using dlib and pre-trained IMDB dataset.

Sentiment Analysis on the IMDB dataset using BERT, Hugging Face and PyTorch

A python script for downloading IMDb image (SenseTime clean face datasets) with multi processing.

IMDB Classification using BERT and Hugging Face

The Internet Movie Database (IMDb) is a website that serves as an online database of world cinema. This website contains a large number of public data on films such as the title of the film, the year of release of the film, the genre of the film, the audience, the rating of critics, the duration of the film, the summary of the film, actors, directors and much more. Faced with the large amount of data available on this site, I thought that it would be interesting to analyze the movies data on the IMDb website between the year 2000 and the year 2017.

Analysis of the Olivetti Faces dataset using various machine learning and deep learning methods. Along with sentiment analysis of the IMDB Movie Review Dataset employing models ranging from Naive Bayes to Recurrent Neural Networks (RNNs), including data augmentation techniques.

This project demonstrates fine-tuning a pre-trained DistilBERT model using LoRA (Low-Rank Adaptation) for sentiment analysis on a truncated IMDb dataset. It leverages Hugging Face's transformers, peft, and datasets libraries to build an efficient text classification pipeline.

本项目基于 PyTorch 和 Hugging Face 的 Transformers 库，使用预训练 BERT 模型对 IMDb 电影评论数据进行二分类情感分析（正面 / 负面）。

Age, Gender predictor using facial features. Face and Eye detection by Haar Cascade OpenCV and Prediction using WideResNet model trained on IMDB-WIKI Dataset.

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The code of download IMDb-Face dataset

Twitter Parsing I've recently discovered the Chris Albon Machine Learning flash cards and I want to download those flash cards but the official Twitter API has a limit rate of 2 weeks old tweets so I had to find a way to bypass this limitation : use Selenium and PhantomJS. Purpose of this project : Check every 2 hours, if he posted new flash cards. In this case, download them and send me a summary email. Face Recognition Modern face recognition with deep learning and HOG algorithm. Using dlib C++ library, I have a quick face recognition tool using few pictures (20 per person). Playing with Soccer data As a soccer fan and a data passionate, I wanted to play and analyze with soccer data. I don't know currently what's the aim of this project but I will parse data from diverse websites, for differents teams and differents players. NYC Taxi Trips Kaggle playground to predict the total ride duration of taxi trips in New York City. Kaggle Understanding the Amazon from Space Use satellite data to track the human footprint in the Amazon rainforest. Deep Learning model (using Keras) to label satellite images. Predicting IMDB movie rating Project inspired by Chuan Sun work How can we tell the greatness of a movie ? Scrapping and Machine Learning

Download IMDB-Face DataSet

The objective of the project is to predict the age of person based on their face image. Pytorch was used to train a Convolutional deep Neural Network with face images from IMDB/WIKI dataset on a kaggle platform. Accuracy for different CNN architectures with different hyper parameters setting was evaluated.

Real-time face detection and emotion/gender classification using fer2013/imdb datasets and openCV.

A Lightweight, Production-Ready & End to End Sentiment Analysis Pipeline Based on IMDb Reviews, Featuring a Flask Web App, Dockerized Deployment, and a Hugging Face Spaces Online Demo

Explore the world of sentiment analysis with this project utilizing the DistilBERT model, PyTorch, and the Hugging Face Transformers library. The model is finely tuned on a dataset featuring 10,000 IMDB movie reviews, offering robust sentiment classification.

This repository contains a custom sentiment analysis model fine-tuned for movie reviews. Built on Hugging Face Transformers and pre-trained on IMDB and Rotten Tomatoes datasets, this model is optimized for classifying text as positive or negative with high accuracy.

This project challenged us to process and integrate data coming in from a variety of sources - IMDb data, movie rating data from MovieLens, and The Numbers data. We utilized multiple features of the Talend and SQL server to optimize the complete ETL process We then visualized the integrated data from our dimensional model in #Tableau and #PowerBI dashboards showcasing some core KPIs and metrics. This project helped us understand the various challenges faced while building data integration pipelines and business intelligence applications.

Using wideRestnet to get proper with dataset of imdb face

Classifies the imdb-wiki face dataset using Python.

Sentiment Classification Of IMDB Reviews with BERT & Hugging Face

A modular NLP pipeline for binary sentiment classification on IMDb movie reviews using Hugging Face Transformers. The project demonstrates scalable model evaluation, multilingual compatibility (tabularisai), and clean engineering practices.

This project demonstrates sentiment analysis on the IMDb dataset using Hugging Face's `transformers` library. The model is based on DistilBERT, a smaller, faster, and lighter version of BERT. The goal of this project is to classify IMDb movie reviews as either positive or negative using the DistilBERT model for binary classification.

Neural Network trained on IMDB-WIKI faces database to predict age and gender

Fine-tuning a DistilBERT model for sentiment analysis on IMDb reviews using Hugging Face Transformers.

A hands-on implementation of a sentiment analysis model using the IMDb dataset and Hugging Face Transformers