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Machine Learning: Regression(으)로 돌아가기

워싱턴 대학교의 Machine Learning: Regression 학습자 리뷰 및 피드백

4,471개의 평가
839개의 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 808개 리뷰 중 76~100

교육 기관: Kowndinya V

Apr 01, 2018

This course gives deeper understanding of regression concepts. There were insights that are really helpful esp related to interpretation of coefficients. IMO, these insights are not obvious. Provides insights into different regression choices that are available along with their pros and cons.

교육 기관: Raul O

Mar 25, 2016

Incredible course!

I totally recommend it

교육 기관: Tanmay G

Feb 21, 2016

Fantastic course in regression, taught with the mathematical rigor necessary to really understand (not just use) the concepts. The instructors both do an amazing job introducing the concepts piece by piece in a logical and easy to follow manner. In addition, several modules have *optional* in depth derivations of key formulae for those who want to understand the mathematical underpinnings of the regression methods

교육 기관: Wenxin X

Mar 12, 2016

Learned a lot! Now I have been acquired a basic understanding of machine learning! Materials are not much, so it's not painful to accept. Recommended for everybody interested in this topic!

교육 기관: Andrei U

Jun 27, 2016

Very good course.

교육 기관: Suoyuan S

Jan 21, 2016

Good course, but could improve the quiz. Currently the quiz are too easy for ML learners.

교육 기관: Sahil D

May 16, 2016

Good overall theoretical and practical explanation of the material, I was also able to use scikit learn and pandas without any difficulties instead of graphlab create.

교육 기관: Pawan K S

Feb 13, 2016

This course is very detailed and have lot of information about regression, should be taken by anyone who wants to become master in it. But each lesson should be given a week, otherwise it becomes over whelming. Assignments are good as well, though some of them should have better instruction.

There should have been a programming assignment on kernal regression as well, as it is one of the upcoming technique.

교육 기관: Amar B

Sep 25, 2017

Very in depth for someone looking to go into detail.

교육 기관: Radomir N

Feb 22, 2016

Very nice and engaging course!

교육 기관: Katalin S

Jan 30, 2016

Exceptionally well done course

교육 기관: Miguel M d B

Mar 20, 2016

Excellent course! Provides great overview of regression techniques.

교육 기관: Erkan E

May 20, 2017


교육 기관: Stefano T

Feb 10, 2016

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

교육 기관: Oleksii R

Jun 04, 2016

Great course. Thanks a lot.

교육 기관: Fernando F

Jan 12, 2016

I think this course has been very interesting. Regression is too wide for covering entirely in a course like this but it has provided me with the basic knowledge and fundamentals to keep working in the matter.

교육 기관: Asim I

Dec 19, 2015

Awesome. Pure awesome. Great presentation on the theory and all the assignments force you to code solutions from scratch, you're not dependent on Graphlab. Very detailed presentation of advanced topics not covered in other superficial introductions to regression. And practical advice from the instructors shows that they are imparting practical real-world advice on running regression.

교육 기관: prabal k

Aug 23, 2017

Very good flow of the content.

교육 기관: Benoit P

Dec 29, 2016

This whole specialization is an outstanding program: the instructors are entertaining, and they strike the right balance between theory and practice. Even though I consider myself quite literate in statistics and numerical optimization, I learned several new techniques that I was able to directly apply in various part of my job. We really go in depth: while other classes I've taken limit themselves to an inventory of available techniques, in this specialization I get to implement key techniques from scratch. Highly, highly recommended.

FYI: the Python level required is really minimal, and the total time commitment is around 4 hours per week.

교육 기관: Trong T L

May 24, 2016

Great intro to regression

교육 기관: charan S

Jul 22, 2017

Amazing course which intuitive knowledge base. I personally liked the analysis part of every concept and algorithm via curves. This interpretation is very rare in most of the courses. Thanks for a such a beautiful course. And even the implementation via python graphLab was a good practise to learn.

교육 기관: Dipanjan S

May 15, 2016

Excellent lectures with great explanations for the concepts as well as the mathematical equations and derivations. The assignments and concrete implementations also really helped reinforce the same concepts and to get a better idea of how it can be used to solve real world problem. Really amazing!

교육 기관: Happy-Learner

Jan 17, 2016

I saw a number of machine courses that are with too general contents and more like conference presentations. It's hard to learn and grasp something from them. However this is a real Machine Course that provides informative, appropriate details and derivations from which I can learn and understand the meaning and insights buried in math symbols and equations. No doubt, the optional video lectures are excellent enhanced "nutrition." Looking forward to the three courses in this specialization. Thanks, Profs. Emily Fox and Carlos Guestrin, for instructing such wonderful authentic courses.

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: Antonio d R

Jan 07, 2016

It's a great course.