Learn about getting the most out of your training data by using cross-validation techniques.

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Supervising the data

When using supervised learning, think of the data scientist as a teacher and the machine (e.g., a laptop) as a student. As a teacher supervises students’ learning, the data scientist supervises the machine learning process.

The goal is to teach students in the most effective way possible. Given the many teaching techniques available, how does a teacher know which are successful?

In a word—testing.

However, good teachers don’t jump into testing. Good teachers provide students with opportunities to practice what they have learned.

Let’s say a teacher has developed a bank of 100 questions with answers that can help students practice and evaluate their learning via testing. The following image provides a couple of examples of how these questions can be used:

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