Unlock Your Next Favorite Film! Our NLP-powered Movie Recommendation Web App delivers tailored suggestions based on cast, genres, and production companies. Explore a seamless Streamlit interface, also, you can see the description of selected movie. and all movies list.

This case study shows how to create a model for text analysis and classification and deploy it as a web service in Azure cloud in order to automatically classify support tickets. This project is a proof of concept made by Microsoft (Commercial Software Engineering team) in collaboration with Endava http://endava.com/en

Hire the Perfect candidate. HackerEarth Competitions solution.

Graduation Project/Sentiment Analysis in Turkish Film Reviews

What is the difference between a data scientist and a data analyst? An NLP approach.

A Machine Learning Model that detects different language syntax.

Text classification using various techniques, including Naive Bayes and Passive Aggressive classifiers, along with different vectorization methods such as Count Vectorization

Captionate - Image Captioning Toolkit

This project aims to develop a machine learning algorithm that can accurately detect and filter out spam comments on YouTube videos.

Proteins have different family types, this modal determine a protein's family type based on sequence. Inspired by search engines such as BLAST which has this capability, but it want to try out and see if a machine learning approach can do a good job in classifying a protein's family based on the protein sequence.

NLP-powered recommendations using cosine similarity on film metadata.

Basic Pipeline for comprehensive Text Classification

Content Based Movie Recommender

This Machine learning powered Recommendation Engine suggests Movies for a user based on the user's past intrests by content based filtering. In this ML model the attributes of movies like genres , cast , director , description are taken into consideration while being converted into vector format. The cosine distance is found between the vectors …

The provided code snippet performs movie recommendation based on movie metadata using the TMDB Movie Metadata dataset from Kaggle.

This project is a Spam Detection System built using Python. It classifies SMS messages as spam or ham (not spam) using machine learning techniques.

Topic extraction from tweets with Latent Dirichlet Allocation (LDA).

Rating: (6/10) The project uses Python libraries and APIs to analyze Reddit data, predict user input, suggest new titles based on cosine similarity, calculate combined scores, and output the best suggestion.

📚 Book and 📺 TV Series Recommendation System by using Qt Designer and SQLite

This repository contains the code that I used to do spam detection