Question:
b. Identify and explain FOUR differences between machine learning and statistical learning.

Answer:

1. Purpose:
   • Machine Learning: Primarily used for prediction and focuses on building algorithms that allow computers to learn from data.
   • Statistical Learning: Focuses on understanding the relationship between variables and building models based on statistical principles.
2. Data Size:
   • Machine Learning: Works well with large datasets and is optimized for handling big data.
   • Statistical Learning: Typically designed for smaller datasets, and its methods may struggle with large-scale data.
3. Assumptions:
   • Machine Learning: Fewer assumptions about the underlying data distribution. It relies more on empirical learning and experience.
   • Statistical Learning: Often based on strong assumptions regarding the data, such as normality, linearity, and homoscedasticity.
4. Flexibility:
   • Machine Learning: Highly flexible, can adapt to various data types and is often used for unstructured data like images, audio, and text.
   • Statistical Learning: More rigid and typically applied to structured, well-defined datasets with clear variables.