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Exploratory Data Analysis of Olympic games, using the Seaborn library. The first step was to clean the data, then to examine it and finally to visualize the data in order to make the necessary conclusions.

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data-analysis data-science exploratory-data-analysis olympic-games python statistical-analysis

120-years-od-olympic-games-exploratory-analysis-python's Introduction

  • ๐Ÿ‘‹ Hi, Iโ€™m @PanicMilica
  • ๐Ÿ‘€ Iโ€™m interested in Projects in Python.
  • ๐ŸŒฑ Iโ€™m currently learning Machine Learning Algorithms.
  • ๐Ÿ’ž๏ธ Iโ€™m looking to collaborate on new projects based on AI, ML and DL.
  • ๐Ÿ“ซ How to reach me [email protected]

For prediction of car price I used Simple Linear Regression, Multiple Linear Regression and Decision tree. There were two main goals that I wanted to do in this project. Firstly, I wanted to estimate the price of cars by taking into account a set of features, based on historical data. Secondly and most importantly is that by developing models I wanted to accurately predict car price based on its features, in order to make informed purchases. I implemented and evaluated various methods on a dataset consisting of prices of different makes and models. Results show that Multiple Linear Regression using Ordinary Least Squares (OLS) method gives really good results.

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