This repository explores the analysis and prediction of financial time series data using various machine learning and deep learning techniques. The project focuses on understanding historical index data, extracting meaningful features, and applying regression models and deep learning architectures for forecasting

Analyzed 5,000+ movies with Pandas and Colab to build a machine learning model predicting movie revenue.

This project aims to provide a comprehensive analysis of three different machine learning problems: classification, clustering, and regression. By utilizing publicly available datasets, we explore essential steps in machine learning workflows, including data preprocessing, feature selection, model training, and evaluation. The purpose is to showcas