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

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


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


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:

2701 — 2725 de 3,049 Avaliações para o Fundações do aprendizado de máquina: uma abordagem por estudo de caso

por Arish A

8 de jun de 2016

por Mario A G J

26 de abr de 2016

por Weiyi W

11 de jun de 2018

por Mehul P

1 de ago de 2017

por Jijo T

6 de out de 2015

por Mazen A

9 de out de 2016

por Rishabh C

23 de jul de 2020

por Rakesh G

15 de abr de 2019


15 de abr de 2020

por Mahesh B

10 de out de 2019

por Poornima S

18 de fev de 2019

por Hyeong R J

2 de fev de 2017

por Marcos M M

24 de ago de 2017


15 de abr de 2021


30 de jun de 2018

por Vinicius G d O

23 de jun de 2016

por José T G R

1 de nov de 2015

por Tushar A

13 de jul de 2020

por Fernando S

20 de ago de 2017

por Godwin

4 de jun de 2017

por Annie I R

4 de jan de 2016

por Mayur S

18 de jan de 2017

por Shikhar S

8 de dez de 2020

por Wridheeman B

30 de jun de 2020

por Eric S

5 de jan de 2016