Data Preprocessing for Data Science

What you'll learn

• The concepts of domain and range in data science.
• To split data into training and testing sets.
• Determine the accuracy of your machine learning models.
• Apply min-max scaling and Z-score standardization.
• Use PCA for dimensionality reduction.
• Find hidden patterns in your data using Factor Analysis.
• Visualize high-dimensional data using t-SNE.