Supervised Learning Basics Quiz

• Supervised learning is a process of an algorithm learning from a training dataset to approximate a mapping function from input to output.
• supervised learning can be broken down into two types: classification and regression.
• Classification problems are when the output variable is a category, such as “red” or “blue”. Regression problems are when the output variable is a real value, such as “dollars” or “weight”.
• There are many different supervised learning algorithms, each suited for a specific type of problem.
• supervised learning is used in a variety of applications, including recommendation and time series prediction.

Test your knowledge on the fundamentals of supervised learning, including classification, regression, and different algorithms. Explore the applications of supervised learning in recommendation systems and time series prediction.