Chevron Left
返回到 Machine Learning: Regression

学生对 华盛顿大学 提供的 Machine Learning: Regression 的评价和反馈

4.8
5,474 个评分
1,016 条评论

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

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!

筛选依据:

276 - Machine Learning: Regression 的 300 个评论(共 983 个)

创建者 Rama K R N R G

Aug 19, 2017

I really liked the progression of the topics and coverage. Good presentation with good amount of details/depth in each topic.

创建者 akashkr1498

Mar 28, 2019

please take care while framing assignment and quize question it is very difficult to understand what exactly u want us to do

创建者 Ji H K

Aug 13, 2020

This is a great course to understand the knowledge and concept of regression and also there are very useful practical quiz.

创建者 Evaldas B

Nov 28, 2017

Very good and accurate course about regresion. Not just the basics but a lot of things you can use in real life chalenges.

创建者 Syed A R

Jan 10, 2016

Exceptional course!. Emily went into great details of the regression algorithms and its application. Thoroughly enjoyed it.

创建者 George G

Oct 10, 2018

The course provided many useful insights on Regression techniques, and provided in depth understanding of the task in hand

创建者 LAVSEN D

Jul 30, 2016

A very good introduction to Machine Learning: Regression, covering the wide range of topics and explanations in lucid way.

创建者 Sanjeev B

Jan 10, 2016

Great instructors! Wish the problem sets were tougher and required more deeper thinking and choice of techniques to apply.

创建者 Rajesh V

Jan 30, 2017

This course has a very detailed explanation of regression and quizzes which evaluates your understanding of the material.

创建者 Aaron

May 2, 2020

Good introduction to regression with many crucial concepts, very friendly to the new learner on machine learning domain.

创建者 venkatpullela

Oct 26, 2016

The course is really good. The quizzes and support is really bad as they slow you down and distract with useless issues.

创建者 Renato R S

Feb 19, 2016

A very well designed course. I would recommend to anyone with serious goals on learning regression and machine learning.

创建者 Min K

Sep 14, 2017

Thank you very much to Instructor "Emily and Carlos" for such an excellent and very informative course on regression :)

创建者 abhay k

Sep 13, 2019

What I was trying to get at my starting stage in ML for last 2 months, this course given in 2 weeks.

Thank you coursera

创建者 Oscar J

May 16, 2019

Step by Step about Regression explained well and easy to understand. Mandatory course for every data science begginer.

创建者 Kishaan J

May 30, 2017

Talks about each and every nitty-gritty details of the different types of Regression algorithms that are in use today!

创建者 Ruben S

Feb 7, 2016

Great course which covers most of regression topics and important thigns such as lasso regression or ridge regression.

创建者 Matthias B

Jan 3, 2016

Great Course, well structured and following a clear path. Would enjoy some more of the optional technical backgrounds!

创建者 Barnett F

Sep 6, 2016

Bingo course, I learned two years ago ,but I just know the concepts, do not know how to code it ,now this course,,,,,

创建者 Bipin A

Jul 26, 2020

I was very satisfied by the way the courses are taught. And the assignments are not boringly easy. Would recommend.

创建者 Rahul M

Feb 27, 2016

It is an awesome Course For Beginners. But I wanted it to be in R since it is more easier to implement things in R.

创建者 Jonathan L

Jan 14, 2016

Visualization of ridge regression and lasso solution path in week 5 is worth the cost of the entire specialization.

创建者 Devasri L

Apr 10, 2020

Very helpful course. I sincerely thank Coursera and University of Washington to provide this opportunity to learn.

创建者 Deepak K S

Nov 18, 2016

Great Course! Complex things explained in simple ways. Challenging Assignments helped in reinforcing the concepts.

创建者 Maxwell N M

Apr 7, 2016

Lasso is very cool for dimension reduction i discover another algorithm powerfull than Personal Component Analysis