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Understanding Machine Learning

An introduction to machine learning with no coding involved.

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2 Horas12 Videos36 Exercises
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Descrição do Curso

Gain an Introduction to Machine Learning Concepts

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.

You will explore basic yet essential concepts to start your machine learning journey, using hands-on exercises to cement your knowledge. This includes developing an understanding beyond the jargon and learning how this exciting technology powers everything from self-driving cars to your personal Amazon shopping suggestions.

Explore the Machine Learning Basics

How does machine learning work, when can you use it, and what is the difference between AI and machine learning? This course covers all of these topics.

You’ll start by unpacking what machine learning is, exploring its basic definition and its relation to data science and artificial intelligence. Then, you will familiarize yourself with its vocabulary and end with the machine learning workflow for building models.

We wrap up the course by digging deeper into deep learning. You will explore two common use cases for deep learning: computer vision and natural language processing (NLP), and acknowledge the limits and dangers of machine learning.
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  1. 1

    What is Machine Learning?

    Livre

    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.

    Reproduzir Capítulo Agora
    What is machine learning?
    50 xp
    Generating movie recommendations
    50 xp
    AI, data science, and machine learning walk into a bar...
    50 xp
    What's true about machine learning?
    100 xp
    Machine learning concepts
    50 xp
    Machine learning lingo
    100 xp
    Supervised vs unsupervised
    50 xp
    Machine learning workflow
    50 xp
    Steps for building a model
    100 xp
    A true step
    50 xp
  2. 2

    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.

    Reproduzir Capítulo Agora
    Supervised learning
    50 xp
    Warm up
    50 xp
    Regressing with class
    100 xp
    Unsupervised learning
    50 xp
    We don't need no supervision
    100 xp
    Gotta cluster 'em all!
    50 xp
    Evaluating performance
    50 xp
    True or false?
    100 xp
    Land of confusion
    50 xp
    Improving performance
    50 xp
    It's a long way to the top
    100 xp
    Explore hyperparameter tuning
    50 xp
  3. 3

    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.

    Reproduzir Capítulo Agora
    Deep learning
    50 xp
    What is deep learning?
    100 xp
    Should I use deep learning?
    50 xp
    Computer vision
    50 xp
    Image data
    50 xp
    The process
    100 xp
    Natural Language Processing
    50 xp
    Sentiment analysis
    50 xp
    Classifying machine learning tasks
    100 xp
    Bag of words
    50 xp
    Limits of machine learning
    50 xp
    To black box or not to black box?
    100 xp
    Spotting bias in machine learning
    50 xp
    Congratulations!
    50 xp
For Business

GroupTraining 2 or more people?

Get your team access to the full DataCamp library, with centralized reporting, assignments, projects and more

Nas seguintes faixas

Certificação disponível

Fundamentos de IA

Ir para a trilha

Compreensão dos tópicos de dados

Ir para a trilha
Lis Sulmont HeadshotLis Sulmont

Content Program Manager at Duolingo

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