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Machine Learning: Regression(으)로 돌아가기

워싱턴 대학교의 Machine Learning: Regression 학습자 리뷰 및 피드백

4.8
4,409개의 평가
832개의 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 251~275

교육 기관: Hemant V G

Mar 14, 2016

Course has covered regression in sufficient details and gave practical aspect of it. Thanks to Emily for very good content and teaching

교육 기관: Med N

Jan 11, 2016

One of the best courses I have taken!

Very good balance of depth and breadth of the material.

교육 기관: Peter G

Feb 26, 2016

Excellent presentation of fundamental concepts and good overview of some specific methods.

교육 기관: Rodolfo S

Jun 08, 2016

It's a really good course. I congratulate you.

교육 기관: LAVSEN D

Jul 30, 2016

A very good introduction to Machine Learning: Regression, covering the wide range of topics and explanations in lucid way.

교육 기관: Cal D

Dec 19, 2015

A few minor glitches with the homework assignments so far. Hopefully this is only because it is the first time the class is being offered.

I love the instructors. Great enthusiasm and both clearly love what they do. Inspiring for data scientists in training.

교육 기관: Mai T T

Jun 26, 2016

Great content and very well instructions

교육 기관: FilippoV

Sep 03, 2017

very good

교육 기관: David H

May 31, 2016

Congrats to Carlos and Emily on producing a great course. As a humble software developer with no statistics background (and someone who hasn't used calculus since they left school nearly 30 years ago) I found this course to be very accessible, the concepts clearly explained, and the results of the course work have been rewarding. Thanks for kick-starting my little grey cells again.

교육 기관: Patrick M

Feb 01, 2016

A great course that will take you way past what you may remember of linear regression from high school or college days. This course is part math, part algorithms and part application (in Python). I loved it. The instructors are good and the material is generally well presented (I took the course the first time through, so there seemed to be a few gaps / rough edges.)

This course may be intimidating if you don't like mathematical notation, or if you have never used Python before. It may also be challenging if your high school / college freshman calculus is rusty. The concepts aren't super hard (basic statistics, integration, differentiation, matrix math but with multi-variate twists), but you will need to think carefully through some lessons to appreciate them.

The online tests are good - and the instructions for each week's problems are detailed. There is enough guidance to clearly show what needs to be done, but enough gaps to bridge that you're made to think about the problem at hand.

교육 기관: zhengqian z

Feb 02, 2017

Really good course, let me know a lot about the topic.

교육 기관: Chokdee S

Apr 16, 2017

This is one of my favorite courses for ML, The best course for learning regression stuffs ever. I really love it.

교육 기관: Daniel V

Jun 10, 2016

I do not this regression :D

Honestly, I can not thank Carlos and Emily enough given such a solid and casual understanding.

I am looking forward to every new Session and ofcourse the Capstone. But still a long way there, which is good news, more time with Carlos and Emily... yeah!

교육 기관: Alfred G

Jun 29, 2016

I strongly recommended you guys to walk through this course. It worth it! And the programming assignment is awesome. I also recommended that you can try to use sklearn + pandas + numpy to rebuild your code.

교육 기관: TONGHONG C

Jun 14, 2017

Best ML course I've ever taken!

교육 기관: Daniel Z

Mar 08, 2016

The most important aspects of regression are approached clear and precise

교육 기관: Do H L

Jan 14, 2016

All the courses in this specializations are very well-made and rigorous. I think all MOOCs, especially techinical ones, should be as well-designed as this or even more.

교육 기관: Daniel R

Feb 07, 2016

The detail level of the regression covered in this course is absolutely necessary if you want to achieve an outstanding level in the Machine Learning area.

The teacher is awesome and the capacity of making it simple for everyone is really from another planet! The best course I have taken so far!

교육 기관: Pau D

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!

교육 기관: Asif N

Jul 05, 2017

I love the teaching style of Emily. Her pronunciation is very clear and her short series of videos develops my interest more and more. The first course of this specialization made my interest to complete the specialization. I love the case study methodology that clarified all my confusion remained after attending the class.

교육 기관: Alberto V

Apr 08, 2017

A wonderful course about regression. Strongly recommended.

교육 기관: Dzmitry D

Jan 06, 2016

Thank you! It was fantastic!

교육 기관: Ed S

Mar 02, 2018

You will get a good grasp of Linear Regression, Ridge Regression, Lasso and potential use for feature selection, gradient descent, coordinate descent, numpy and graphlab create

교육 기관: 李真

Feb 20, 2016

Great

교육 기관: Guomao X

Sep 20, 2016

the material is solid and using python is a good way to learn machine learning programming