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Machine Learning: Regression(으)로 돌아가기

워싱턴 대학교의 Machine Learning: Regression 학습자 리뷰 및 피드백

4.8
4,377개의 평가
827개의 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 797개 리뷰 중 76~100

교육 기관: Thuong D H

Mar 05, 2016

Good course

교육 기관: Veer A S

Mar 21, 2018

Excellent course to learn about Regression models.

교육 기관: Carlos F A

Jun 09, 2016

I already knew how to do linear regression before taking this course; however, I had always struggled to understand how ridge and lasso regression worked and what their usefulness was; thanks to this course I was finally able to understand those concepts very well. The visual explanation of how the ridge and lasso regression work made this course well worth its time.

교육 기관: Gabor S

Jan 17, 2017

This a well thought out course. From the simple concepts it gradually takes you to the more complex ones. The quizzes and programming assignments help you to really understand the problems that were introduced in the videos. The video slides of every module can be downloaded as a pdf document which makes the material easily searchable. And last but not least Emily Fox is a great instructor.

교육 기관: Nilesh K

Jul 18, 2016

very good coverage of a wide range of topics. impressive!

교육 기관: Matthias B

Jan 03, 2016

Great Course, well structured and following a clear path. Would enjoy some more of the optional technical backgrounds!

교육 기관: Roopam K

Jul 26, 2017

excellent course. good pace and good assignments

교육 기관: Leonardo J T G

Aug 23, 2016

The best !!

교육 기관: Ziyue Z

Aug 10, 2016

Great course! Excellent overview of the goal of regression, and the difference between L1 and L2 regularization, as well as some generally applicable machine learning concepts/algorithms. Packed with material and very worthwhile.

교육 기관: David E

Jun 14, 2016

great class. Challenging but worth it.

교육 기관: Marcus C

Feb 08, 2016

great in depth course on regression. I really enjoyed the implementations of different algorithms all by myself.

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: Suresh A

Apr 19, 2016

Fantastic course.

Lot of courses I have taken do not give the mathematical formulation. This course provides a detailed understanding of the math behind ML.

Also in the programming exercises one implements the algorithms from scratch and also use the existing libraries.

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: Filipe G

Mar 12, 2016

The best Machine learning course I ever took. I compare it very favourably to Jeff Leek's course, or Andew Ng's course - which are both good in their own right.

A lot of effort went into making this a really good course. I very much recommend it.

교육 기관: Miguel M d B

Mar 20, 2016

Excellent course! Provides great overview of regression techniques.