1. Unit Introduction

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Welcome to “Introduction to Machine Learning!”

In this set of lessons, you will explore machine learning and how it is used in the world around you.

Machine learning is the science of using data to train computers so that they can make decisions, perform tasks automatically, and improve from experience.

It focuses on developing computer programs that learn from the data they are given.

Data is a collection of facts and information.

It can consist of numbers, words, measurements, observations, and more.

Every time you use technology, you create data.

For example, you create data when you: Shop online Do research for a school paper Or take an online quiz.

Even not doing things -- such as choosing not to open an email or not to click on an ad -- creates data.

You also create data when you are offline.

For instance, when you walk into a business And buy a product.

Because there is so much data available, it’s impossible for humans to analyze it all.

For instance, imagine if an employee at a video-streaming company had to go through every customer’s entire watch list to recommend other movies they might enjoy!

Instead, the video-streaming company relies on machines for help.

Computers are given data -- called “training data” -- which computers learn from.

Over time, they use this information to improve experiences for users.

You have probably heard of several types of machine learning, such as: Self driving cars, Speech-recognition technology, And facial-recognition technology.

Smart machines and applications such as these are popular because they help people and companies make quicker, more accurate decisions.

As a result, today’s businesses are investing more money in machine learning, and the number of jobs related to this technology continues to grow.

In the following lessons, you will explore machine learning in four different ways.

In lesson one, you will look at a pretend person’s driving records.

You will use Google Maps to help you compile this data and make inferences about the user’s preferences based on the simulated driving habits.

In the second lesson, you will create a survey in Google Forms to collect data about people’s likes and dislikes.

Then, you will create a model to predict how much someone will like a different product.

For example, you could try to predict whether someone will enjoy a book based on how they rate different book genres.

In the third lesson, you will explore how computers learn based on the data they receive.

You will use a machine learning app to teach a computer about a set of images.

Then, you will see how accurately the computer identifies other images.

Finally, you will consider the benefits and drawbacks of machine learning for real-world decision-making.

As you complete this lesson, you will keep a journal in a digital document to reflect on what you discover about machine learning and its implications.

Now, move on to the next video to get started!