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워싱턴 대학교의 Machine Learning: Regression 학습자 리뷰 및 피드백

4.8
4,414개의 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

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 802개 리뷰 중 126~150

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.

교육 기관: Joanna T L

Mar 14, 2016

Excellent, step-by-step introduction to regression. The instructor takes her time to make sure every step is explained with details.

교육 기관: Bui T T (

Jan 17, 2016

What a great course about machine learning I've been taken so far! One of the best thing (I like) for this course is that I have deep understanding and I am able to implement the machine learning algorithms by myself.

교육 기관: Enrique J A R

Dec 29, 2015

I enjoyed specially the part about performance assessment and cross validation.

교육 기관: Aaron B

Feb 14, 2016

great course, lots of wonderful hands on material, excellent lectures.

교육 기관: Fernando B

Feb 21, 2017

Best Course on ML yet on the Web

교육 기관: Antonio P L

Dec 30, 2015

Fantastic course and really complete about regression.

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: Zhao Y

Feb 27, 2016

Excellent instructor!

The concepts, though hard, are well explained in a clear and organized manner.

The assignments are very practical and helper.

교육 기관: Joseph K

Dec 05, 2015

I've studied machine learning quite a bit in school as well as on my own, but I wish this class was how I learned the first time around. Everything is explained so clearly and well-balanced between practical understanding vs underlying theory. Definitely serves as a good review for those of us who are looking to get back into machine learning!

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: Jair d M F

Jan 08, 2016

Very cool. Thanks!

교육 기관: Arjunil P

Oct 02, 2016

Exquisite course. A lot of content was covered quite thoroughly.

교육 기관: Erik E

Mar 15, 2018

Very good course.

교육 기관: Jonathan A A

Feb 16, 2017

Excellent course, you'll get value for your money

교육 기관: Matic D B

Feb 09, 2016

Great and representative course.

교육 기관: shoubhik b

Jan 31, 2017

Very thorough. If you are beginner this course will give you the tools to do further study by yourself. I still go back to the lectures to refresh a few concept. Really sad that course 5 and 6 won't be released :(

교육 기관: Fahim K

Jan 06, 2016

The course is really helpful. It has started with simple Regression model and gradually build the different advance regression model. Thanks for this wonderful course.

교육 기관: Richard N B A

Feb 02, 2016

Great course! Not simply a machine learning black box tutorial - like a few courses out there - but delves into the mathematics behind the algorithms (with several optional, more advanced excursions provided) and requires that we actually implement a few of the ideas ourselves.

교육 기관: RAMESH K M

Mar 06, 2016

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