Project overview
In this project, you’ll assume the role of a sports data scientist working to predict match winners in the English Premier League (EPL). You’ll use machine learning techniques with Python and the scikit-learn library to build predictive models based on historical match data from the 2020-2021 and 2021-2022 seasons.
This project will enhance your machine learning portfolio, demonstrating skills in data preparation, feature engineering, model training and evaluation, and working with time series data. You’ll learn how to improve model performance through techniques like computing rolling averages. By the end, you’ll have a functioning model to predict EPL match winners.
Objective: Use machine learning with Python and scikit-learn to predict English Premier League match winners based on historical data.
Key skill required
To complete this project, it's recommended to build these foundational skills in Python
- Working with pandas DataFrames to load, explore, and manipulate data
- Understanding concepts of features, targets, training, and evaluation in machine learning
- Preparing data for machine learning by cleaning it and engineering relevant features
- Training and evaluating the performance of machine learning models
Projects steps
Step 1: Project Overview
Step 2: Investigating Missing Data
Step 3: Cleaning Data for Machine Learning
Step 4: Creating Predictors for Machine Learning
Step 5: Training an Initial ML Model
Step 6: Improving the Model with Rolling Averages
Step 7: Retraining Our Model
Step 8: Combining Home and Away Predictions
Step 9: Next Steps
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