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Voltar para Machine Learning: Regression

Comentários e feedback de alunos de Machine Learning: Regression da instituição Universidade de Washington

4.8
estrelas
5,463 classificações
•
1,015 avaliações

Sobre o curso

Case Study - Predicting Housing Prices In our first case study, predicting house prices, you will create models that predict a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,...). This is just one of the many places where regression can be applied. Other applications range from predicting health outcomes in medicine, stock prices in finance, and power usage in high-performance computing, to analyzing which regulators are important for gene expression. In this course, you will explore regularized linear regression models for the task of prediction and feature selection. You will be able to handle very large sets of features and select between models of various complexity. You will also analyze the impact of aspects of your data -- such as outliers -- on your selected models and predictions. To fit these models, you will implement optimization algorithms that scale to large datasets. Learning Outcomes: By the end of this course, you will be able to: -Describe the input and output of a regression model. -Compare and contrast bias and variance when modeling data. -Estimate model parameters using optimization algorithms. -Tune parameters with cross validation. -Analyze the performance of the model. -Describe the notion of sparsity and how LASSO leads to sparse solutions. -Deploy methods to select between models. -Exploit the model to form predictions. -Build a regression model to predict prices using a housing dataset. -Implement these techniques in Python....

Melhores avaliações

PD

16 de mar de 2016

I really enjoyed all the concepts and implementations I did along this course....except during the Lasso module. I found this module harder than the others but very interesting as well. Great course!

KM

4 de mai de 2020

Excellent professor. Fundamentals and math are provided as well. Very good notebooks for the assignments...it’s just that turicreate library that caused some issues, however the course deserves a 5/5

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576 — 600 de 982 Avaliações para o Machine Learning: Regression

por tonghong c

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14 de jun de 2017

Best ML course I've ever taken!

por 易灿

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28 de nov de 2016

课程很生动，讲的也很详细！如果能提供些相关算法的资料就更好了！

por Konstantin G

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8 de fev de 2016

It's cool! I love your courses!

por Kim K L

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3 de jan de 2016

Great course ... learned a lot!

por Brian N

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20 de mai de 2018

Good to learn again this topic

por prabal k

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23 de ago de 2017

Very good flow of the content.

por Lionel T L

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15 de abr de 2017

complete, explicite, rich code

por Shiva R

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20 de nov de 2016

Concepts explained in detailed

por 童哲明

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12 de jun de 2016

Kernel regression还是有许多不太清楚的地方！

por Radomir N

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21 de fev de 2016

Very nice and engaging course!

por Katalin S

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30 de jan de 2016

Exceptionally well done course

por Nicolas T

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18 de dez de 2015

Best Machine learning mooc !!!

por Israel d S R d A

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18 de fev de 2020

Great course very recommended

por Harsh C

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17 de out de 2019

Teaches me lots of new things

por Lanqing B

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26 de set de 2017

Well structured and designed.

por 林玮

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24 de out de 2016

这门课提供了一个新的角度，从而使我更深刻地理解了回归预测。

por 江智彬

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27 de fev de 2016

The teachers are very funny !

por Vijai K S

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7 de dez de 2015

It is a very thorough course.

por Yash A

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20 de mai de 2020

Simply the best course ever.

por Xi C

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21 de mai de 2019

Very intuitive explanations!

por Deleted A

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1 de mai de 2019

Great course, great material

por Jorge C

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17 de dez de 2017

Very good indepth expanation

por Mithilesh K S

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22 de out de 2017

awesome approach of teaching

por Dmitriy D

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6 de jan de 2016

Thank you! It was fantastic!

por Hanna L

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12 de ago de 2019

Thanks for the great class!

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