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Machine Learning for Business

Understand the fundamentals of Machine Learning and how it's applied in the business world.

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2 Horas15 Videos48 Ejercicios
28.725 AprendicesTrophyDeclaración de cumplimiento

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Descripción del curso

Learn the Basics of Machine Learning


This course will introduce the key elements of machine learning to the business leaders. We will focus on the key insights and base practices how to structure business questions as modeling projects with the machine learning teams.

Dive into the Model Specifics


You will understand the different types of models, what kind of business questions they help answer, or what kind of opportunities they can uncover, also learn to identify situations where machine learning should NOT be applied, which is equally important. You will understand the difference between inference and prediction, predicting probability and amounts, and how using unsupervised learning can help build meaningful customer segmentation strategy.
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  1. 1

    Machine learning and data use cases

    Gratuito

    Machine learning is used in many different industries and fields. It can fundamentally improve the business if applied correctly. This chapter outlines machine learning use cases, job roles and how they fit in the data needs pyramid.

    Reproducir Capítulo Ahora
    Machine learning and data pyramid
    50 xp
    Terminology clarification
    50 xp
    Order data pyramid needs
    100 xp
    Match tasks in data pyramid
    100 xp
    Machine learning principles
    50 xp
    Modeling types
    50 xp
    Find supervised and unsupervised cases
    100 xp
    Job roles, tools and technologies
    50 xp
    Job role responsibilities
    50 xp
    Match data projects with job roles
    100 xp
    Team structure types
    100 xp
  2. 4

    Managing machine learning projects

    This chapter will look into the best and worst practices of managing machine learning projects. We will identify most common machine learning mistakes, learn how to manage communication between the business and ML teams and finally address the challenges when deploying machine learning models to production.

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En las siguientes pistas

Científico de datos en PythonCientífico de datos en RHabilidades informáticas para las empresas

Colaboradores

Collaborator's avatar
Hadrien Lacroix
Collaborator's avatar
Sara Billen
Karolis Urbonas HeadshotKarolis Urbonas

Head of Machine Learning and Science

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