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Machine Learning: Regression(으)로 돌아가기

워싱턴 대학교의 Machine Learning: Regression 학습자 리뷰 및 피드백

4,457개의 평가
838개의 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 807개 리뷰 중 26~50

교육 기관: Ling Z

Apr 09, 2019

I took this class long time ago and just revisited it today. Compared to other online class, this class has a lot details. I am satisfied with both the clarity and depth of the content.

교육 기관: Christopher M

Jan 26, 2019

Great course. You get to write the algorithms for OLS regressions, ridge regression, lasso regression, and for k-nearest neighbor models. The instruction even includes some optional graduate-level videos on with more detailed explanations of how more advanced algorithms for solving the regressions may be developed (eg, subgradients for lasso regression).

교육 기관: Aayush A

Jul 12, 2018

This course is very good.I learnt a lot from it about regression.very recommended for all trying to get expert in machine learning.

교육 기관: mahesh

Jul 13, 2018

The best course, I feel better and confident at regression concepts by the end of the course.

교육 기관: Theo L

Jan 05, 2016

This course was well structured and well executed. I thoroughly enjoyed and was challenged by the material in the course. I appreciated the assignment/quiz approach to deal with such dense topics. I can see where people who have backgrounds in a number of the topics discussed throughout the course could feel there was too much hand holding, but I found the level of hints/help in the assignments were at the right level for me to work through & gain deeper understanding for the material presented.

My one criticism of the course stems from the denseness of the material. I believe there is an opportunity to introduce more quizzes after various sections within each module. It would be best to make these quizzes optional in order not to turn off more advance students, but I believe it would be beneficial for those students who do not have much, or any, experience in these topics to have more opportunities to test and gain deeper understanding in the material just covered.

Overall, solid course!

교육 기관: Sanjay M

Jun 24, 2017

Excellent foundational course .

교육 기관: Binil K

Jul 04, 2017

nice course!!

교육 기관: Aadesh N

Jun 14, 2016

Great course materials

교육 기관: Mudambi S S

Feb 10, 2016

The best course on Machine Learning so far!

교육 기관: Tripat S

Jan 11, 2016

This is the best course in ML...Prof Carlos and Prof Fox are the best ....Would recommend for evryone

교육 기관: Abhinav U

Jan 11, 2016

Great course, very detailed and hands on, also including appropriate amount of mathematical rigour to help you understand what is going on under the hood. Highly recommended. I specially liked the modules on Ridge regression and Lasso regression, really well done.

교육 기관: ELINGUI P U

Mar 31, 2016

Emilie is a great teacher

교육 기관: Jerome G

Jan 07, 2016

Thanks Emily and Carlos, it was a very great moment when light come in !

교육 기관: Sergey M

Jan 19, 2016

A very good course! Especially that scikit-learn can be used as framework for solving assignments and at the same time exercises for programming of learning algorithms from scratch. Thanks!

교육 기관: Pandu R

Jan 06, 2016

Another great course in the series. I can't wait for the 3rd to start!

교육 기관: Georgios D

Oct 04, 2016

Absolutely amazing.

교육 기관: Farooq M K

Nov 09, 2016

The very best by our instructor Emily Fox. Cannot be easier than this

교육 기관: Vaidas A

Feb 07, 2016

This course is great! I had a lot of fun going through the exercises and concepts they show are really relevant. I am not sure about the level of the whole series, as it probably is more towards beginner than intermediate, but it's great to get some practice with Python and learn / brush-up / deepen knowledge in ML.

I am really looking forward to the next class - that's probably the area I would like this series to improve, the gaps between courses are just too long.

Overall great work!


교육 기관: Andrew M O

Mar 29, 2016


교육 기관: Willismar M C

Oct 14, 2016

Amazing course, I enjoined the talking about the linear model, regularization, gradient descent in how to optimize the weights . In special I enjoyed so much the OPTIONAL videos talking more details of some aspects of machine learning like bias and variance. I am very pleased to have completed this course. Thank you.

교육 기관: Lech G

Jan 06, 2016

This is probably the best Coursera course I have completed so far (and I am kind of Coursera junkie). very well structured, the right amount of math and driven by the experiments on the real data.

Looking forward to Classification course and others in series.

교육 기관: James L

Feb 01, 2016

Great look under the hood of common regression techniques.

교육 기관: Sara E E

Mar 22, 2018

I could give this course 6 out of 5 stars

교육 기관: Tomasz J

Jan 06, 2016

Excellent in depth dive into Regression! Great profs!

교육 기관: Hongbing K

Jan 02, 2016

Very clear and thorough explanation on regression and implementation details. The closed-form calculation and comparison against gradient descent is excellent.