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Machine Learning: Regression(으)로 돌아가기

워싱턴 대학교의 Machine Learning: Regression 학습자 리뷰 및 피드백

4,415개의 평가
833개의 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


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!


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 803개 리뷰 중 251~275

교육 기관: Bernardo N

Jan 16, 2016

Best Regression MOCC available online! Also consider the whole Machine Learning specialization, one of the best series you can find on this subject

교육 기관: ngoduyvu

Feb 16, 2016


교육 기관: Aniruddha B

Feb 13, 2016


교육 기관: Marcus V M d S

Oct 07, 2017

Thank you for all the effort you put in the exercises and the data. It was a great course! Perhaps you could put references for further study of the topics?

교육 기관: Nihar S

Apr 21, 2016

Great class that breaks down machine learning concepts into simple digestible pieces.

교육 기관: Harley J

Jul 18, 2017

Very solid course for understanding machine learning principles, including developing methodical approaches to solving data problems.

교육 기관: 李扬骏

Apr 11, 2016

Good for everybody!

교육 기관: Juncheng P

Mar 07, 2017

a very detailed courses on regression

교육 기관: ChristopherKing

Aug 02, 2016


교육 기관: Jorge S N

Feb 22, 2016

I liked very much the way this course is structured. Simple and complete. Very well done.

교육 기관: Kim K L

Jan 03, 2016

Great course ... learned a lot!

교육 기관: rahul

Dec 31, 2017

Awesome Course!!!!

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: Lionel T L

Apr 16, 2017

complete, explicite, rich code

교육 기관: Sarah W

Aug 09, 2017

Great course! Well paced, learned a lot! Topics are well-explained.

교육 기관: Chia-Sheng L

Jan 04, 2016

This course offer many aspects like graphic comparison or detail math explanation help us understand more easily what a model or method means. The teacher have great effort on material design.

교육 기관: Tuhin

Sep 15, 2016

One of the best courses in Regression Modelling.

교육 기관: Thomas E

May 12, 2016

A bit to easy to get through the exercises but otherwise very enlightening and inspirering.

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: Matthew M

Jan 05, 2016

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

교육 기관: Josiah N

Sep 28, 2016

Nice explanation of concepts, and very helpful with getting started on the programming assignments. The algorithms are explained well in pseudo code, and the instructor does a good job at explaining why they work the way they do. The math is not very challenging, so I never felt frustrated.

I only wish there was not such an emphasis on Graphlab. Although they do allow you to use other methods to finish the assignments, it feels as though more attention is given to explaining how Graphlab works instead of standard, free python libraries. I understand that they're trying to push a product, but I don't want to pay for something I'll only be using for a few courses. More attention should be given to sklearn.

교육 기관: Rashi K

Dec 28, 2015

This was a great course and had in depth insights on a single topic. Worth doing.

교육 기관: Vaibhav O

Jan 03, 2017

Excellent course on Regression! Must do for some serious hands on in the field

교육 기관: Dong Z

Jan 01, 2016

Best course! really!!!

교육 기관: Popovics L

Dec 29, 2015

Harder than the previous course, but helps to understand machine learning regression in deep.