IBM: Guided Project: Predict World Cup Soccer Results with ML
In this beginner-friendly, hands-on guided project, develop your data science and machine learning skills in under an hour by building a prediction model for the 2022 FIFA World Cup. Perfect for anyone interested in learning more about prediction models.
There is one session available:
Guided Project: Predict World Cup Soccer Results with ML
About this courseSkip About this course
Machine learning has changed the game for sports predictions. Popular Python libraries like LIME and SHAP are used to interpret and explain models. Even if you are not a soccer fan or working in the sports industry, machine learning skills are in demand in many industries. The skills needed to import and use data to create predictive models are both practical and valuable.
In this hands-on guided project, you’ll develop practical Python, pandas, numpy, sklearn, seaborn, matplotlib, seaborn, LIME, and SHAP skills to process data using the 2022 World Cup teams’ data. Then, you’ll train a model to predict the outcome of the group stages.
After completing this project, you will have practical experience working with Python machine-learning tools.
Get started fast. This hands-on guided project uses a browser-accessible development environment with the technologies and libraries you need, preinstalled—including the Python IDE—saving you setup time and complications. Also, note that this platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer, or Safari.
At a glance
- Language: English
- Video Transcript: English
- Associated skills: Predictive Modeling, Machine Learning, Scikit-learn (Machine Learning Library), Firefox, NumPy, Seaborn, Data Science, Development Environment, Forecasting, Pandas (Python Package), Matplotlib, Python (Programming Language), Microsoft Internet Explorer
What you'll learnSkip What you'll learn
After completing this hands-on guided project, you’ll be able to:
- Choose and collect the data to import into the project
- Clean data for a machine learning project
- Understand objects needed for a machine learning project
- Use machine learning to predict sports games
- Analyze machine learning model using LIME and SHAP