Popular GitHub Repositories for Imdb Webscrapping

Keras implementation of a CNN network for age and gender estimation

Multi-task learning smile detection, age and gender classification on GENKI4k, IMDB-Wiki dataset.

Using Bert/Roberta + LSTM/GRU/BiLSTM/TextCNN to do the sentiment analysis on the imdb datasets.

Computer Vision module for detecting emotion, age and gender of a person in any given image, video or real time webcam. A custom VGG16 model was developed and trained on open source facial datasets downloaded from Kaggle and IMDB. OpenCV,dlib & keras were used to aid facial detection and video processing. The final system can detect the emotion, age and gender of people in any given image, video or real time webcam

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

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.

Sentiment analysis in Pytorch on an IMDb dataset.

Deep-Atrous-CNN-Text-Network: End-to-end word level model for sentiment analysis and other text classifications

Sentiment Analysis using Stochastic Gradient Descent on 50,000 Movie Reviews Compiled from the IMDB Dataset

FP-Age: Leveraging Face Parsing Attention for Facial Age Estimation in the Wild

Implementation of the methods proposed in **Adversarial Training Methods for Semi-Supervised Text Classification** on IMDB dataset (without pre-training)

Movie Recommendation Chatbot provides information about a movie like plot, genre, revenue, budget, imdb rating, imdb links, etc. The model was trained with Kaggle’s movies metadata dataset. To give a recommendation of similar movies, Cosine Similarity and TFID vectorizer were used. Slack API was used to provide a Front End for the chatbot. IBM Watson was used to link the Python code for Natural Language Processing with the front end hosted on Slack API. Libraries like nltk, sklearn, pandas and nlp were used to perform Natural Language Processing and cater to user queries and responses.

The objective of this project is to scarp the data from IMDb website and form an analysis that will help data analyst or production company to decide how they are going to proceed with making a new movie, second is to form a model to predict what are the sentiments of movies based on user reviews.

Text Classification using Mamba Model

[EMNLP2019] Rethinking Attribute Representation and Injection for Sentiment Classification

Pytorch implementation of the paper Convolutional Neural Networks for Sentence 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%.

[ACL2018] Cold-Start Aware User and Product Attention for Sentiment Classification

BERT-IMDB电影评论情感分类实战：SwanLab可视化训练

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.