Chevron Left
Voltar para Fundações do aprendizado de máquina: uma abordagem por estudo de caso

Comentários e feedback de alunos de Fundações do aprendizado de máquina: uma abordagem por estudo de caso da instituição Universidade de Washington

4.6
estrelas
13,101 classificações

Sobre o curso

Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems? In this course, you will get hands-on experience with machine learning from a series of practical case-studies. At the end of the first course you will have studied how to predict house prices based on house-level features, analyze sentiment from user reviews, retrieve documents of interest, recommend products, and search for images. Through hands-on practice with these use cases, you will be able to apply machine learning methods in a wide range of domains. This first course treats the machine learning method as a black box. Using this abstraction, you will focus on understanding tasks of interest, matching these tasks to machine learning tools, and assessing the quality of the output. In subsequent courses, you will delve into the components of this black box by examining models and algorithms. Together, these pieces form the machine learning pipeline, which you will use in developing intelligent applications. Learning Outcomes: By the end of this course, you will be able to: -Identify potential applications of machine learning in practice. -Describe the core differences in analyses enabled by regression, classification, and clustering. -Select the appropriate machine learning task for a potential application. -Apply regression, classification, clustering, retrieval, recommender systems, and deep learning. -Represent your data as features to serve as input to machine learning models. -Assess the model quality in terms of relevant error metrics for each task. -Utilize a dataset to fit a model to analyze new data. -Build an end-to-end application that uses machine learning at its core. -Implement these techniques in Python....

Melhores avaliações

BL

16 de out de 2016

Very good overview of ML. The GraphLab api wasn't that bad, and also it was very wise of the instructors to allow the use of other ML packages. Overall i enjoyed it very much and also leaned very much

PM

18 de ago de 2019

The course was well designed and delivered by all the trainers with the help of case study and great examples.

The forums and discussions were really useful and helpful while doing the assignments.

Filtrar por:

76 — 100 de 3,049 Avaliações para o Fundações do aprendizado de máquina: uma abordagem por estudo de caso

por Peter F

•

30 de mar de 2020

por Rithik S

•

26 de mai de 2020

por Yakubu A

•

23 de dez de 2020

por ye

•

31 de jan de 2021

por Jitendra S

•

29 de abr de 2016

por Ashutosh N

•

30 de mai de 2020

por Krupesh A

•

15 de fev de 2019

por Shreyash N S

•

20 de mai de 2020

por Japman S

•

6 de jun de 2020

por YM C

•

6 de set de 2019

por Darren R

•

13 de out de 2015

por Kaushik M

•

1 de mai de 2016

por D. F

•

2 de fev de 2021

por Rohit

•

19 de abr de 2020

por Shibhikkiran D

•

13 de abr de 2019

por Diogo P

•

15 de fev de 2016

por Karthik M

•

27 de dez de 2018

por Alexandru B

•

21 de jan de 2016

por Mallikarjuna R V

•

17 de jan de 2019

por Sundar R

•

19 de ago de 2020

por akashkr1498

•

18 de jan de 2019

por Yuvraj S

•

1 de fev de 2019

por Jaime R

•

17 de dez de 2018

por Ezequiel P

•

7 de nov de 2020

por Ayush G

•

5 de jun de 2020

Coursera Footer

Comece ou impulsione sua carreira

Procurar temas populares

Cursos e artigos populares

Consiga um diploma ou certificado on-line

Coursera

Comunidade

Mais

Aprenda em qualquer lugar
Placeholder
Placeholder
Placeholder