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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

13,083 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.

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2901 — 2925 de 3,043 Avaliações para o Fundações do aprendizado de máquina: uma abordagem por estudo de caso

por Julien F

16 de nov de 2017

Some quiz questions were vague and/or ambiguous, or not covered in talks.

por Marco M

4 de dez de 2015

Too much synthetic on very important parts, too much focused on graphlab

por Alejandro V

13 de nov de 2020

TuriCreate is not the apropriate tool for practical Machine Learning

por Pawan K S

15 de mai de 2016

Nice introductory course but too much dependence on graphLab create

por Jesse W

24 de dez de 2016

It is better if allow me upgrade only when I finished this course.

por Tushar k

30 de nov de 2015

Good course to begin machine learning with but it's too easy !!

por Konstantinos L

8 de jan de 2018

Nice course but too easy. Assignments should be more difficult

por Seong H M

25 de set de 2021

Problems and files and videos not updated base on the changes

por Felipe A S S

23 de jan de 2021

The libraries used on the course are a little bit unsopported

por Nadeem B

27 de jul de 2021

Concepts and explanation is great but using outdated modules

por Atharv J

14 de set de 2020

The course should be taught in pandas rather than graphlab.

por Max F

10 de jan de 2016

Not a bad course, but extremely basic. Was expecting more.

por Adrien L

2 de fev de 2017

No good without the missing course and capstone projects

por Aleksey C

11 de dez de 2016

....mmm fsdfg gsgsd sgsdgsdg sdsdgsdg ggsgsd sgdsdgsg


15 de jun de 2020

Installing software parts gave me a very hard time.

por Bastian M P

1 de jun de 2016

Could go a little more in detail on the algorithms.

por Jaime O

31 de jan de 2017

The Deep Learning part needs to be improved

por Chen S

26 de out de 2015

Very basic, the quizzes aren't clear enough

por Li-Pu C

29 de out de 2020

A little bit too easy, but good for rookie

por Harsh V K

8 de mai de 2019

Should use Python 3 instead of Python 2

por Phú L L H

3 de abr de 2021

sofware guideline is quiet useless

por Yu G

7 de fev de 2021

No idea what to write here...

por Jorge C

29 de mai de 2016

It is a very simple course.

por Ricardo S

10 de ago de 2021

Feels a bit out dated


25 de jun de 2020

Good for knowledge