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学生对 University of Washington 提供的 Machine Learning: Regression 的评价和反馈

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5,581 个评分

课程概述

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....

热门审阅

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

EV

Jun 24, 2016

An in-depth overview of the regression techniques and models. I think it went as deep into the concepts as I wanted it to go. Being a developer I found it quite understandable, and useful.Keep it up!

筛选依据：

326 - Machine Learning: Regression 的 350 个评论（共 1,001 个）

创建者 Giovanni B

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Dec 25, 2015

I think this course is great, Emily and Carlos explain things so clearly and provide excellent material

创建者 יונתן ה

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Nov 27, 2021

Great course. Good assignments - python implementations, different than the known Stanford's ML course

创建者 Alexis C

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May 8, 2016

very intuitive explanations. learned a lot, despite having taken many machine learning classes before.

创建者 Tripat S

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Jan 10, 2016

This is the best course in ML...Prof Carlos and Prof Fox are the best ....Would recommend for evryone

创建者 Arnold A

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May 6, 2017

It is really useful and an eye-opening course, especially if you are interested in machine learning.

创建者 Taehee J

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Sep 13, 2016

I like this course since it teaches the fundamental concept of regression with hands-on programming.

创建者 Chandan N

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Feb 16, 2025

Excellent excellent course, right amount of detail, good assignments, the presenters are very good.

创建者 Yin X

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Sep 9, 2017

Best course I have had so far on regression at Coursera. Thaaaaaank you Coursera and Washington U!

创建者 Milan C

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Apr 10, 2017

Very nice course. The course gave me a good overview in how deep you can dive even with regression.

创建者 juan f r s

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May 15, 2016

Excelent course and very well explained. Many thanks to both of you Emily and Carlos. All the best

创建者 Ramesh K

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Mar 6, 2016

Lectures and assignments were awesome thanks to the professor for making this easier to understand.

创建者 Tahereh R

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Apr 2, 2019

Thorough explanations of the essential concepts are provided! Valuable course and lectures.

Thanks!

创建者 Shalini S

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Apr 18, 2016

Great course! The course material was very well designed. Carlos and Emily are excellent teachers.

创建者 Viet N

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Jan 17, 2016

It's very interesting and challenging course, especially at the end. Thank you for your knowledge!

创建者 Matthew M

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Jan 5, 2016

This course is an ideal mixture of theory, practical application, and coding. I really enjoyed it.

创建者 Rui W

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Jul 16, 2016

Some practical skill and some theoretical knowledge are bought to me. I am so glad to enjoy them.

创建者 Stefano T

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Feb 10, 2016

Very interesting course showing in a clear and easy to follow way the key concepts of Regression.

创建者 Omar B

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Feb 1, 2017

Great course !

The best thing is when Emily talks about the intuition of each model or algorithm.

创建者 Rafael A

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Feb 22, 2016

Once more, excellent delivery by Emily and Carlos. Looking forward to the classification course.

创建者 An i

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Jul 23, 2023

It is very very helpful to learn new topic in machine learning

Thank you coursera and Emily fox

创建者 Nagendra R

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Jun 25, 2020

excellent course on regression. each and every concept is clear and in depth.Thank you Coursera

创建者 쥬

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May 24, 2016

This course helped me a lot to understand regression. Now I can apply this idea to my own work.

创建者 Michaël L

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Mar 30, 2016

Excellent course with lots of hands on !

The teacher is excellent and provide clear explanation.

创建者 Bokai C

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Mar 21, 2016

Excellent Lectures!

Suggestions: homework results should be more representative and distinctive.

创建者 Aziz D

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Jul 16, 2021

Awesome course thank you so much for this valuable informations and good comprehinsive content