In the context of K-Nearest Neighbors (KNN) in supervised learning, and how does it make predictions?

A social media manager wants to show the proportion of users by device type (iOS, Android, Web). Use:

A restaurant recommendation system considers user preferences and similarity to other users. This is an example of:

Before implementing an AI solution, a business conducts a readiness assessment. This process examines whether the organization has the proper foundation and support for real-world deployment. What are they evaluating?

What is the primary function of Linear Regression in supervised learning, and how does it work in predicting outcomes like the price of a house?

A navigation app calculates the fastest route using rules like IF traffic is heavy THEN reroute. This is:

What is the primary goal of normalization and scaling in data transformation, and what is an example of a technique used for normalization?

A real estate company wants to estimate the selling price of a house based on its square footage, number of bedrooms, and location. What type of algorithm should be used?

A numeric feature “Age” has values ranging from 5 to 90. You want to scale it between 0 and 1 so all features contribute fairly to modeling. Which transformation is appropriate?

If your model performs poorly (low accuracy or high error), what is one simple step you can try first?