Course Description
This chapter will introduce machine learning and its two main categories—supervised and unsupervised. You’ll learn about what they are and how they are used. You’ll also learn about how machine learning is related to artificial intelligence. The importance of data will be discussed and explained in this chapter. This chapter will also explain the difference between classification and regression for machine learning.
What You'll Learn
- Understand what machine learning is and how it is used
- Distinguish between supervised and unsupervised learning
- Explain the difference between classification and regression
- Describe how machine learning relates to artificial intelligence
- Recognize the importance of data in machine learning
- Get started with JupyterLab for machine learning work
Key Takeaways
- Machine learning has two main categories: supervised learning and unsupervised learning.
- Machine learning is related to artificial intelligence.
- Data is important to machine learning and its applications.
- Classification and regression are different approaches used in machine learning.
- The chapter introduces what machine learning is and how it is used.
Frequently Asked Questions
What does this course cover?
This chapter introduces machine learning and its two main categories, supervised and unsupervised learning, including what they are and how they are used. It also covers how machine learning relates to artificial intelligence, the importance of data, and the difference between classification and regression.
What are the learning objectives of this course?
The objectives are to understand what machine learning is and to understand the difference between classification and regression.
What topics are included in the lessons?
Lessons include Introduction to JupyterLab, Machine Learning and Its Uses, Machine Learning and Artificial Intelligence, Classification vs. Regression, Importance of Data, and Unsupervised Learning vs. Supervised Learning.
What skills does this course help develop?
It covers machine learning, machine learning algorithms, machine learning methods, automated machine learning, supervised learning, and unsupervised learning.
