Tennis Ace My Python Supervised Machine Learning ‘challenging’ Project From: The Codecademy Data Science course Machine Learning section, supervised machine learning. Project: Using supervise machine learning model predict what it takes to be one of the best tennis players in the world. ---------------------------------------------------------------------------------------- Project Requirements: Python v3 or later: https://www.python.org/ scikit https://scikit-learn.org/ Pandas https://pandas.pydata.org/ Matplotlib https://matplotlib.org/ Jupyter notebook: https://jupyter.org/ ---------------------------------------------------------------------------------------- Overview: This project is slightly different than others you can encountered on Codecademy. Instead of a step-by-step tutorial, this project contains a series of open-ended requirements which describe the project. Project Goals: Create a linear regression model that predicts the outcome for a tennis player based on their playing habits. By analyzing and modeling the Association of Tennis Professionals (ATP) data, you will determine what it takes to be one of the best tennis players in the world. Prerequisites: In order to complete this project, you should have completed the Linear Regression and Multiple Linear Regression lessons in the Machine Learning Course. Using Jupyter Notebook as the project code presentation is a personal preference, not a project requirement. Requirements: Using supervised machine learning models, test the data to better understand what it takes to be an all-star tennis player. ---------------------------------------------------------------------------------------- Links: tennis_ace Blog Presentation https://www.alex-ricciardi.com/post/tennis-ace ---------------------------------------------------------------------------------------- Project map: Python jupiter notebook code lines file: tennis_ace.ipynp Python code lines file: tennis_ace.py data files: data/*.csv chart images: graph/*.png ---------------------------------------------------------------------------------------- My Project layout: - Investigation and analyses of the given data - Simple Linear Regression (given data) - Supervised Machine Learning Single Feature Linear Regression Models Multiple Features Linear Regression Models
ARiccGitHub/tennis_ace
My Python Supervised Machine Learning ‘challenging’ Project From: The Codecademy Data Science course Machine Learning section, supervised machine learning
Jupyter Notebook