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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
5,328 classificações
994 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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751 — 775 de 961 Avaliações para o Machine Learning: Regression

por Prabal G

20 de Out de 2020

great

por Md. T U B

26 de Ago de 2020

great

por SUJAY P

21 de Ago de 2020

great

por Subhadip P

4 de Ago de 2020

great

por Douba J

30 de Mai de 2020

YEAHH

por FOTSING K H C

4 de Ago de 2019

great

por 李真

19 de Fev de 2016

Great

por Vaibhav K

20 de Set de 2020

good

por YASA S K R

31 de Ago de 2020

good

por ANKAN M

16 de Ago de 2020

nice

por Saurabh A

19 de Jul de 2020

good

por Keyur M

9 de Jun de 2020

good

por Vaibhav S

16 de Mai de 2020

Good

por Vansh S

10 de Mai de 2019

nice

por 王曾

25 de Set de 2017

good

por Birbal

13 de Out de 2016

good

por FW Y

16 de Ago de 2017

做中学

por Ablaikhan N

14 de Mar de 2021

A+

por Ganji R

8 de Nov de 2018

E

por Anunathan G S

28 de Ago de 2018

L

por IDOWU H A

20 de Mai de 2018

I

por Ruchi S

8 de Nov de 2017

e

por Alessandro B

27 de Set de 2017

e

por Navinkumar

17 de Fev de 2017

g

por ngoduyvu

16 de Fev de 2016

v