Chevron Left
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 101~125

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: 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: 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: 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.

교육 기관: Abishek R

Feb 29, 2016

Extremely well planned and prepared. Thank you for the course.

교육 기관: Ganesan P

Jun 20, 2016

Very good course to get the foundations right. Emily has done an excellent job in explaining the material and she reinforces the concepts with examples. I strongly believe this course will provide the required skills to explore further topics in this area. Great Job and thanks to Coursera for providing us this platform.

교육 기관: vishnu v

Jan 03, 2016

Great course on regression. Covers almost all aspects on how to build a regression model from scratch, also covers few advanced topics aswell.

교육 기관: qi l

Aug 01, 2016

Lovely lectures with easy to follow up mathematics

교육 기관: Soumya

Mar 05, 2016

a little more details considering the the cost of the module would be appreciatiated

교육 기관: Juan C A

Jan 09, 2016

This is an excellent course! Emily Fox does an excellent job at explaining what could be a hard concept grasp. I am talking about convex optimization and the LASSO solution. I have taken graduate level classes in convex optimization and the math is high level and can be challenging. The animation Emily presents along with the geometric intuitive explanation drives the intuition home. Thank you Emily and Carlos for this class.

교육 기관: Badrinath J

May 03, 2016

The best

교육 기관: Chengye Z

Nov 28, 2016

It's a very helpful course. I really have leart a lot, by both watching video and programming.

교육 기관: Zhihui X

Feb 19, 2016

Great course!!! Thank you.