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學生對 华盛顿大学 提供的 Machine Learning: Regression 的評價和反饋

4.8
5,480 個評分

課程概述

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....

熱門審閱

PD

2016年3月16日

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!

KM

2020年5月4日

Excellent professor. Fundamentals and math are provided as well. Very good notebooks for the assignments...it’s just that turicreate library that caused some issues, however the course deserves a 5/5

篩選依據:

876 - Machine Learning: Regression 的 900 個評論(共 984 個)

創建者 Oleg S

2017年10月10日

...really challenging...

...have to be a real statistician and pythonist...

...need time to absorb new skills...

創建者 Moises V

2016年3月24日

This course is well structured. It covered a good parts of details I was missing on my machine learning path.

創建者 Ayswarya S

2019年2月5日

Well taught !!Could have been better if practical teaching was more !!I mean teaching via coding was more:)

創建者 Varun R

2016年2月6日

Quite a hard course...

But laid great foundations and reduced the dependence on graphlab.

Thanks Emily!

創建者 林俊凡

2015年12月8日

Good course! Teachers are perfect and knowledge is overall, but the exercise need some improvement.

創建者 Bob

2017年2月6日

Great course. Can only be better if we were taught in the industry standard libraries (fe. SciPy)

創建者 Farrukh N A

2017年1月11日

Overall its a good course on Regression, although its more driven toward mathematics and statics.

創建者 Piyush G

2019年2月25日

The programming assignments were tough ! but the course covers the content very effectively..

創建者 Onwumere O B

2016年3月15日

The course is really well explained and skills obtained are quite valuable in the labor market

創建者 Braden W

2018年8月13日

Great, difficult course. The Graphlab vs scikit thing is the only reason I dock it a star.

創建者 Morgan M

2017年10月13日

Good, well structured. Content can get a bit dense at times, but good to be challenged!

創建者 J G

2018年7月8日

It is a good course, it is really challenging learning how to do it from scratch.

創建者 Steve M

2016年11月17日

A good course overall. at time, the programming assignment is somewhat confusing.

創建者 sandeep d

2020年8月19日

nice theoretical , it would be better if you teach the given notebook examples

創建者 Mridul C

2020年7月20日

It would have been better if the coding part was also covered in videos only.

創建者 sanghoon.lee1@kbfg.com

2020年10月30日

좋은 내용, 자세하고 친절한 설명, 적절한 난의도가 좋았습니다. 다만, 일부 모듈이 윈도우10 환경에서 사용하기 어려운 경우가 있습니다.

創建者 J N B P

2020年10月5日

A really good course which covers the complete concepts of regression models

創建者 Saadullah A

2016年6月23日

Great introductory course for regression analysis and very practical indeed!

創建者 Rafał P

2020年10月11日

Turicreate is a bit confusing. Especially, while having Graphlab in videos

創建者 Sourabh S

2017年3月22日

Course covers in depth many topics. Only some issues with using Pandas.

創建者 Aditya S

2016年7月17日

Good to have deep insight into regression and various popular algorithm

創建者 Charles P

2020年4月8日

Good introduction, very good for basic understanding, but lacks depth.

創建者 Patrick M d F

2019年7月5日

Excellent trad-off between theory, algorithims and practical examples

創建者 Nipun G

2019年4月21日

Please get rid of SFrame and graphlab. However, professor is awesome!

創建者 Andrej

2016年11月13日

Very good course, going through plenty of used regression techniques.