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워싱턴 대학교의 Machine Learning: Regression 학습자 리뷰 및 피드백

4.8
4,286개의 평가
814개의 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!

CM

Jan 27, 2016

I really like the top-down approach of this specialization. The iPython code assignments are very well structured. They are presented in a step-by-step manner while still being challenging and fun!

필터링 기준:

Machine Learning: Regression의 785개 리뷰 중 101~125

교육 기관: Jose A V

Dec 18, 2015

A great course!!! Thanks...

교육 기관: Xiaoyang G

Jan 11, 2016

Thanks

교육 기관: Jinho L

Mar 03, 2016

Very good examples.

교육 기관: Pradeep N

Aug 14, 2016

super one

교육 기관: Lim D K

Feb 15, 2017

Good lecture, nice explanation for statics and machine learning and greate examples

교육 기관: Salim L

Aug 27, 2017

Goes well beyond the statistics that I learned in engineering! Key concepts in regression such Ridge, Lasso and KNN. Use Python to build all your algorithms from the ground up.

교육 기관: 병진 김

May 24, 2016

good!!

교육 기관: Birbal

Oct 13, 2016

good

교육 기관: Kishwar K

Feb 06, 2016

Highly recommended. Perfect Course..

교육 기관: gangan

Jan 01, 2016

Impressive!

교육 기관: Jaisimha S

Dec 14, 2016

Emily is fantastic in explaining abstract math concepts. Thank you!

교육 기관: Marcio R

Feb 23, 2016

This module is very rich in pratical assignments, as well as quizzes to force you to understand what you are doing. Everything is really well balanced, and all the materials are very complete. Is clear the passion from the tutors and teachers in this course. This really gives you the necessary will to proceed, and don't give up, even when things get pretty hard.

교육 기관: Dhanasekar S

Dec 31, 2016

Wonderfully organized and explained. Especially the Lasso and Ridge Regression!

교육 기관: Jabberwoo

Jul 03, 2016

Great teaching, great materials, and a great course!

교육 기관: Borna J

Jun 19, 2016

I love everything about this course. the course material is easy to follow. I also like the coding exercises. I highly recommend the specialisation so far (this is my second course)

교육 기관: Rohit G

Dec 29, 2015

Absolutely loved the way Emily tackled the course content - the knowledge I gained regarding LASSO & RIdge was something even I wasn't expecting. Also the optional video helped a lot to understand the mathematics better as compared to a mechanical write-down of the steps

교육 기관: Wang L

Jan 21, 2016

An Excellent Course, that is able to provide insight and deep understanding about Regression.

교육 기관: Marnix W

Mar 22, 2016

Great course well taught. Amazed about the in depth course material and practices. Thanks!

교육 기관: 王曾

Sep 26, 2017

good

교육 기관: Zynab S

Aug 21, 2016

wonderful course I really enjoyed this topics disscused in this course

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: Saransh A

Oct 12, 2016

This is probably the best course on Regression for ML out there

And this specialisation is probably the best! for Basic Machine Learning... KUDOS!

교육 기관: Kevin K

Oct 31, 2016

Applications and examples are well-chosen. The choice of theory is appropriate given the audience. The problem sets are a tad on the difficult side in that extreme care must be taken to get the right answers. Some of this has to do with how the assignments are structure. Instructions need to be read several times, which can be quite tedious. In the end, they help you learn the material and force you to implement carefully.

교육 기관: Rajkumar K

May 27, 2017

Course was made very intuitive & easy to understand with a case study based approach

교육 기관: Moayyad A Y

Apr 17, 2016

best regression course , full details .