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Learner Reviews & Feedback for Machine Learning: Regression by University of Washington

4.8
stars
5,567 ratings

About the Course

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....

Top reviews

PD

Mar 16, 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

May 4, 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 of 998 Reviews for Machine Learning: Regression

By Jenhau C

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Mar 30, 2019

Great course! Very good insight!

By Fernando B

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Feb 21, 2017

Best Course on ML yet on the Web

By Matic D B

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Feb 9, 2016

Great and representative course.

By Sukwon O

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Dec 5, 2020

Learned a lot from this course.

By DEEP K S

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Aug 30, 2020

can you guys upgrade to python3

By Muhammad Z H

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Aug 29, 2019

Thanks Professor, I learnt alot

By Kunal T

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Dec 19, 2018

Extremely well designed course.

By Sanjay M

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Jun 24, 2017

Excellent foundational course .

By yuanfan p

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Jun 18, 2017

Concise. Hope for more content.

By tonghong c

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Jun 14, 2017

Best ML course I've ever taken!

By 易灿

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Nov 28, 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！

By Kanstantsin H

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Feb 8, 2016

It's cool! I love your courses!

By Kim K L

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Jan 3, 2016

Great course ... learned a lot!

By Brian N

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May 20, 2018

Good to learn again this topic

By prabal k

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Aug 23, 2017

Very good flow of the content.

By Lionel T L

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Apr 15, 2017

complete, explicite, rich code

By Shiva R

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Nov 20, 2016

Concepts explained in detailed

By 童哲明

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Jun 12, 2016

Kernel regression还是有许多不太清楚的地方！

By Radomir N

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Feb 21, 2016

Very nice and engaging course!

By Katalin S

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Jan 30, 2016

Exceptionally well done course

By Nicolas T

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Dec 18, 2015

Best Machine learning mooc !!!

By Israel d S R d A

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Feb 18, 2020

Great course very recommended

By Harsh C

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Oct 17, 2019

Teaches me lots of new things

By Lanqing B

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Sep 26, 2017

Well structured and designed.

By 林玮

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Oct 24, 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。