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

4.8
stars
5,583 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

PH

Apr 7, 2016

This is an excellent course. The presentation is clear, the graphs are very informative, the homework is well-structured and it does not beat around the bush with unnecessary theoretical tangents.

AM

Apr 26, 2020

Very informative, practical course with excellent instructors, I would recommend this course to anyone doing basic machine learning. The only issue I see is that the course can be offered in R.

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926 - 950 of 1,002 Reviews for Machine Learning: Regression

By Yegwende V T

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Feb 8, 2016

Learn more about linear regression, ridge and so on.

By mohinish n

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Mar 22, 2018

Gives good abstraction of underlying algorithm.

By Rushikesh M N

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Nov 20, 2019

Detailed derivation, Loved the way they teach.

By João S

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Jan 7, 2016

Nioce course. Compreensive notes and nice (&fu

By Andy L

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Aug 5, 2017

Great course to get started with regression.

By rajeev r

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Jan 26, 2020

Nice introductory ML concepts to star with.

By shaurya s

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Jan 1, 2016

Excellent course except the last week :)

By mohammed T

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Mar 12, 2018

i wish that you have used scikit learn

By Pier L L

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Sep 20, 2016

Very good course. I really liked it.

By Aman G

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Sep 25, 2018

Don't bug me regarding the review.

By gaozhipeng

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Feb 12, 2016

Nice course! Thank you very much ~

By Paul M

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Dec 23, 2017

Excellent overview. Great slides

By Michael L

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Mar 18, 2017

Far too math, much less practice

By Shashidhar Y

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Mar 1, 2019

Good interactive courses.

By egonigilist

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Aug 18, 2017

several errors in exams

By Jeyaprabu J

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Mar 4, 2016

detailed but slower...

By Gaurav S

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Dec 31, 2015

Good and Insightful

By Mehul P

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Aug 10, 2017

Nicely explained.

By Sandeep K S

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Jan 26, 2016

excellent course

By Qing W

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Dec 6, 2017

actually good

By James H

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Nov 13, 2016

Great course

By Abhishek m

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Jan 23, 2021

nice course

By PHILIPPE R

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Jan 27, 2016

Nice course

By NIGAM P

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Nov 1, 2020

Great Job!

By Rohit K S

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Sep 30, 2020

Nice One!!