Chevron Left
Volver a Machine Learning: Regression

Opiniones y comentarios de aprendices correspondientes a Machine Learning: Regression por parte de Universidad de Washington

4.8
estrellas
5,503 calificaciones

Acerca del 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....

Principales reseñas

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 may. 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

Filtrar por:

51 - 75 de 987 revisiones para Machine Learning: Regression

por Jane z

15 de ene. de 2020

por Ayman K

19 de ene. de 2017

por Tsz W K

25 de abr. de 2017

por Daniel C

15 de mar. de 2016

por Jaiyam S

1 de ene. de 2016

por Juan C A

9 de ene. de 2016

por Kevin K

31 de oct. de 2016

por Samuel d Z

27 de jun. de 2017

por Jatin K

5 de oct. de 2020

por Tanmay G

21 de feb. de 2016

por Nsair A

3 de mar. de 2017

por Pawan K S

13 de feb. de 2016

por Stephane F

31 de dic. de 2015

por Olexandra Z

5 de feb. de 2017

por Gabor S

17 de ene. de 2017

por Leon W

16 de jun. de 2016

por Stefan K

29 de dic. de 2015

por Asim I

19 de dic. de 2015

por David H

31 de may. de 2016

por Philippe N

17 de abr. de 2020

por William C

2 de ene. de 2021

por Jens K

28 de may. de 2018

por Carlos F A

9 de jun. de 2016

por Marcio R

23 de feb. de 2016

por Fahad S

31 de ene. de 2018