Machine Learning: Regression(으)로 돌아가기

# 워싱턴 대학교의 Machine Learning: Regression 학습자 리뷰 및 피드백

4.8
별점
5,080개의 평가
956개의 리뷰

## 강좌 소개

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....

## 최상위 리뷰

KM

May 05, 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 17, 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!

필터링 기준:

## Machine Learning: Regression의 926개 리뷰 중 301~325

교육 기관: Ashutosh A

Feb 09, 2016

Nice illustrations and concepts are explained in clear & concise way through real life examples and data sets.

교육 기관: Barbara X

Feb 02, 2016

This course covers a lot of ground. It not only has hands on practices but also explains the algorithm behind.

교육 기관: Satyam C

Jun 27, 2018

ever best for regression. even better than Andrew NG. Detailed Mathematics explanation is part of this course

교육 기관: NAKKA V S B

Sep 22, 2016

Very good course on Regression but statistical inferences could have been added to give a completion feeling

교육 기관: Yuan L

Aug 08, 2017

A great course covering most of the fundamental concepts and techniques! Very detailed and well explained!

교육 기관: Aliaksandr K

Jan 28, 2017

It's really practical course which covers a lot of main regression concepts and great teachers. Thank you!

교육 기관: Amlan D

Mar 25, 2016

Nice intro to regression! Shorter lectures and more programming challenges would have made it even better.

교육 기관: Kunal B

Jun 02, 2016

This course is awesome. It stimulated my interest throughout the course. Course Material was very useful.

교육 기관: Frank L

Jul 02, 2017

Great Course! Very well explicated and clear. It's a good start for the beginners and not so beginners.

교육 기관: Regis G

Mar 31, 2017

I learnt a lot during this course. The content was very well delivered, and the labs were very helpful.

교육 기관: Giovanni B

Dec 25, 2015

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

교육 기관: Alexis C

May 09, 2016

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

교육 기관: Tripat S

Jan 11, 2016

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

교육 기관: Arnold A

May 06, 2017

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

교육 기관: Taehee J

Sep 13, 2016

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

교육 기관: Yin X

Sep 09, 2017

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

교육 기관: Milan C

Apr 10, 2017

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

교육 기관: juan f r s

May 15, 2016

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

교육 기관: RAMESH K M

Mar 06, 2016

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

교육 기관: Tahereh R

Apr 02, 2019

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

Thanks!

교육 기관: Shalini S K

Apr 18, 2016

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

교육 기관: Nguyen T V

Jan 17, 2016

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

교육 기관: Matthew M

Jan 05, 2016

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

교육 기관: Rui W

Jul 17, 2016

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

교육 기관: Stefano T

Feb 10, 2016

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