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DataCamp

Understanding Machine Learning

via DataCamp

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Overview

An introduction to machine learning with no coding involved.

What's behind the machine learning hype? In this non-technical course, you’ll learn everything you’ve been too afraid to ask about machine learning. There’s no coding required. Hands-on exercises will help you get past the jargon and learn how this exciting technology powers everything from self-driving cars to your personal Amazon shopping suggestions.

How does machine learning work, when can you use it, and what is the difference between AI and machine learning? They’re all covered. Gain skills in this hugely in-demand and influential field, and discover why machine learning is for everyone!

Syllabus

What is Machine Learning?
-In this chapter, we'll define machine learning and its relation to data science and artificial intelligence. Then, we'll unpack important machine learning jargon and end with the machine learning workflow for building models.

Machine Learning Models
-Now that you know the basics of machine learning, let's dive a little bit deeper. At the end of this chapter, you will know the different types of machine learning, as well as how to evaluate and improve your models.

Deep Learning
-In this chapter, we'll unpack deep learning beginning with neural networks. Next, we'll take a closer look at two common use-cases for deep learning: computer vision and natural language processing. We'll wrap up the course discussing the limits and dangers of machine learning.

Taught by

Hadrien Lacroix, Sara Billen and Lis Sulmont

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