About this Repository

The goal of this repository is to use the FIFA 19 Complete Player Dataset to build a machine learning model using supervised learning to determine the top traits with the most influence in creating a top striker.

R^2 Score: 0.863

Published Kaggle Kernel:

• Building a Top Striker in FIFA 19

Model in this Repository:

• Determining the Key Factors for Developing a Top Striker in FIFA

Determining the Key Factors for Developing a Top Striker in FIFA

Problem

The purpose of this repository is to find the top traits that have the most influence in the Finishing score of a footballer so that players can best invest their skill points.

Solution

In order to solve this, we would make use of machine learning python libraries (numpy, pandas,and sklearn) to make a simple exploratory data analysis and visualization. Later, we would make a linear regression model double checking its acurracy with key metrics and finalize with the testing of our model with some values of the found traits.

Dependencies

• Visualization
  • Matplotlib
  • Seaborn
• Data Processing
  • Numpy
  • Pandas
• Regression
  • Sklearn