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Machine Learning: Regression(으)로 돌아가기

워싱턴 대학교의 Machine Learning: Regression 학습자 리뷰 및 피드백

4.8
별점
4,829개의 평가
908개의 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

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!

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

필터링 기준:

Machine Learning: Regression의 877개 리뷰 중 251~275

교육 기관: Jacob M L

Mar 02, 2016

Well presented, practical, and hands-on. By far the best Data Science / Machine Learning series I have taken thus far on Coursera.

교육 기관: Surendar R

Dec 23, 2018

In Depth coverage of lot of concepts, fully enjoyed it! Recommended to anyone wanting to explore in depth concepts of regression.

교육 기관: Abe E

Apr 28, 2017

Excellent. I used some of the videos to prepare and brush up for job interviews. Super helpful to play back at double speed ;-)

교육 기관: Wafic E

Nov 06, 2016

An amazing course. You can sense the effort put into the presentations and assignment work. Loving the specialization thus far.

교육 기관: Sergio D H

Feb 06, 2016

One of the best MOOCs I've ever tried. Great course materials and incredibly talented instructors. I can't recommend it enough.

교육 기관: Luciano S

Aug 07, 2017

I learned a lot of new concepts in this course. It is important to dive deeper than just understing how to use a set of tools.

교육 기관: 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.

교육 기관: 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

교육 기관: 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.

교육 기관: Syed A u R

Jan 11, 2016

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

교육 기관: George G

Oct 10, 2018

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

교육 기관: LAVSEN D

Jul 30, 2016

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

교육 기관: Sanjeev B

Jan 10, 2016

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

교육 기관: Rajesh V

Jan 30, 2017

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

교육 기관: Aaron

May 02, 2020

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

교육 기관: 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.

교육 기관: 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.

교육 기관: Min K

Sep 14, 2017

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

교육 기관: 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

교육 기관: Oscar S

May 16, 2019

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

교육 기관: 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!

교육 기관: Rubén S F

Feb 07, 2016

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

교육 기관: Matthias B

Jan 03, 2016

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

교육 기관: Barnett F

Sep 06, 2016

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

교육 기관: 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.