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explo

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Implemented a flight prediction system using two algorithms, Linear Regression and Decision Trees, to forecast flight prices accurately. The project involved preprocessing and analyzing flight data to extract relevant features such as departure time, destination, and airline. Utilized the Linear Regression algorithm

  • Updated Mar 15, 2024
  • Jupyter Notebook

A codebase for two data analysis projects, both developed using Python. The first project is a GUI application for managing student performance, using Tkinter and csv for input storage and analysis. The second project is a web scraping tool for analyzing movie data from IMDB, using bs4 and pandas for data processing and matplotlib for visualization

  • Updated Jan 1, 2023
  • Python

This project is a hands-on exploration of multiple regression modeling techniques applied to real-world challenges in the context of real estate. It aims to understand how different features influence house or property prices. By utilizing multiple regression models, the project provides insights, decision support, and enhances data science skills.

  • Updated Sep 29, 2023
  • Jupyter Notebook

This notebook explores and analyzes the Heart Disease UCI dataset using Python libraries such as NumPy, Pandas, Matplotlib, Seaborn, and scikit-learn. It includes data visualization, feature engineering, model building using Random Forest Classifier, and evaluation of the model's performance in predicting the presence or absence of heart disease.

  • Updated Apr 9, 2024
  • Jupyter Notebook

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