Learning Outcomes

In this free course, you will learn how to:

• Describe the theory and concepts of principal component analysis (PCA)
• Define the mathematics behind PCA
• Compute required random data to implement PCA without any PCA-specific function in Python and MATLAB
• Analyze PCA outcome by plotting the data accordingly in both Python and MATLAB
• Calculate and implement PCA on Iris datasets in Python using scikit-learn library
• Apply PCA on handwritten digits datasets in Python using scikit-learn library
• Evaluate PCA on Iris datasets in MATLAB using statistics and a machine learning toolbox
• Solve PCA for handwritten digits datasets in MATLAB using statistics and a machine learning toolbox
• Discuss the results of PCA implementation in both Python and MATLAB by plotting the data