Spam Filter AI is a project in Python that uses machine learning to detect spam emails. It uses Natural Language Processing (NLP) and Naive Bayes classification. The program reads email content, converts it into useful data with TF-IDF vectorization, and then decides if the email is spam or not, keeping your inbox clean and organized.

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

Twitter Sentiment Analysis.This repository implements a sentiment analysis model to classify tweets as Positive, Negative, Neutral, or Irrelevant using TF-IDF Vectorization and Random Forest. It includes text preprocessing, tokenization, and data visualizations to explore sentiment distribution.

An end-to-end data science project: load, clean, and analyze news articles, then train and test text classification models using both LinearSVC and Naive Bayes. Evaluate results, interpret key features, and gain actionable insights. The project includes clear code, exploratory data analysis (EDA), and practical suggestions for further improvement.

Implemented a machine learning model to detect fake news using Natural Language Processing techniques like TF-IDF and stemming. Trained multiple classifiers including Logistic Regression and PassiveAggressiveClassifier for accurate classification. This project showcases practical NLP skills for tackling misinformation in media.