Simple web app to classify texts using Flask and HTML. Training of model done on IMDB movie reviews dataset, utilising Hashing Vectorizer.

Topic modeling of IMDB movie reviews dataset using Latent Dirichlet Allocation (LDA).

Simple sentiment analysis of IMDB movie reviews dataset using count vectorizer, Tfidfvectorizer and nltk library.

A browser bookmark which randomly highlights a film to watch on the IMDb watchlist page.

Text Classification using Mamba Model

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.

Dashboard of the top 1000 movies on IMDB (1920-2020)

A deep learning model created to classify the movie reviews as positive or negative.

This projects aims at implementation and training of different orientations and types of Neural Networks with respect to Mathematical equations and problems ranging from a simple straight forward equation to a bit complex equations in nature too. Following a comparative study on how different architectures react with these problems.

Sentiment analysis on the IMDB dataset using Bag of Words models (Unigram, Bigram, Trigram, Bigram with TF-IDF) and Sequence to Sequence models (one-hot vectors, word embeddings, pretrained embeddings like GloVe, and transformers with positional embeddings).

💻 Leveraging the power of SQL to extract actionable insights from complex datasets.

Sentiment classification and opinion prediction based on a movie reviews dataset.

🗨️ This repository contains a collection of notebooks and resources for various NLP tasks using different architectures and frameworks.

build a database from IMDb datasets

RSVP - Movies SQL queries performed on IMDb database to provide recommendations to RSVP Movies based on insights.

Analysis of IMDb datasets

This Git repository features an SQL analysis project for RSVP Movies. It analyzes a dataset to provide insights for their global project releasing in 2022, covering box office performance, genre preferences, actor impact, and release timing. Aimed at delivering actionable recommendations.

Variety of neural network architectures implemented for different datasets and scenarios, along with regularization techniques and hyperparameter tuning strategies.

A simple movie search engine using IMDB data and ElasticSearch.