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

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

Text Classification using Mamba Model

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

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.

This project aims to carry out the in-depth analysis of IMDB movie dataset. Excel is used to draw insights and analyze to find genre, budget, director and more.

Create a personalized movie database with user logins, watch lists, and extensive film details.

A solver for Actorle, the daily actor guessing game

Synchronization of IMDB datasets with Postgres to provide a REST API

It offers an in-depth exploration into classifying IMDB movie reviews using machine learning and NLP techniques. It details steps from data preprocessing and feature extraction to model training with both classical and neural network approaches, aimed at predicting review sentiments.

Implementation of Naive Bayes Classifier for the IMDB reviews dataset

Movies ontology

A Vagrant box that automatically loads the IMDB dataset into Postgres

Transfer Learning models in PyTorch

Using Transformer model to classify IMDb Reviews. Low-level implementation of data preprocessing and tokenization using keras_nlp library