This course is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this course will introduce you to problem definition and data preparation in a machine learning project.
Este curso faz parte do Programa de cursos integrados Machine Learning: Algorithms in the Real World
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Programa de cursos integrados Machine Learning: Algorithms in the Real WorldAlberta Machine Intelligence InstituteInformações sobre o curso
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Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Nível intermediário
Aprox. 7 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Alemão, Russo, Inglês, Espanhol
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Nível intermediário
Aprox. 7 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Alemão, Russo, Inglês, Espanhol
oferecido por
Alberta Machine Intelligence Institute
The Alberta Machine Intelligence Institute (Amii) is home to some of the world’s top talent in machine intelligence. We’re an Alberta-based
Programa - O que você aprenderá com este curso
3 horas para concluir
Introduction to Machine Learning Applications
This week, you will learn about what machine learning (ML) actually is, contrast different problem scenarios, and explore some common misconceptions about ML. You will apply this knowledge by identifying different components essential to a machine learning business solution.
3 horas para concluir
12 vídeos (Total 44 mín.), 6 leituras, 2 testes
2 horas para concluir
Machine Learning in the Real World
This week, you will learn how to translate a business need into a machine learning problem. We'll walk through some applied examples so you can get a feel for what makes a well-defined question for your QuAM. Narrowing down your question and making sure you have the data necessary to learn is critical to ML success!
2 horas para concluir
8 vídeos (Total 34 mín.), 4 leituras, 1 teste
1 hora para concluir
Learning Data
This week is all about data. You will learn about data acquisition and understand the various sources of training data. We'll talk about how much data you need and what pitfalls might arise, including ethical issues.
1 hora para concluir
9 vídeos (Total 34 mín.), 2 leituras, 1 teste
1 hora para concluir
Machine Learning Projects
This week you will learn about the Machine Learning Process Lifecycle (MLPL). After understanding the definitions and components of the MLPL you will analyze the application of the MLPL on a case study.
1 hora para concluir
7 vídeos (Total 35 mín.), 2 leituras, 1 teste
Avaliações
Principais avaliações do INTRODUCTION TO APPLIED MACHINE LEARNING
por SR8 de Out de 2020
I have been teaching Machine Learning for some time now. This course is really good and comprehensively presents the working of machine learning process in a nutshell. Very good introductory course.
por MM28 de Out de 2019
I have really got benefit from this course as a beginner to ML, it gives me the best understanding of ML. I m looking forward to getting into it more efficiently with more practices.
por BW12 de Nov de 2020
An excellent introduction to the mechanics of ML. Not so deep that coding is required, but simultaneously not so high-level as to be abstract. A very nice intro - thanks for this!
por HL21 de Jun de 2020
An excellent introduction to the fascinating world of machine learning and its endless applications. Loved the emphasis on the evaluation of the business prospect of ML as well.
Sobre Programa de cursos integrados Machine Learning: Algorithms in the Real World
This specialization is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this specialization will set you up to define, train, and maintain a successful machine learning application.
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