Guided Project: Predict World Cup Soccer Results with ML V2

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. 3b:T1053,{

• 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

• Basic Python skills
• Access to a web browser