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

5,480 個評分


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....




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!



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


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

創建者 Oleg S


...really challenging...

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

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

創建者 Moises V


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


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

創建者 Varun R


Quite a hard course...

But laid great foundations and reduced the dependence on graphlab.

Thanks Emily!

創建者 林俊凡


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

創建者 Bob


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

創建者 Farrukh N A


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

創建者 Piyush G


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

創建者 Onwumere O B


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

創建者 Braden W


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

創建者 Morgan M


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

創建者 J G


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

創建者 Steve M


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

創建者 sandeep d


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

創建者 Mridul C


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



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創建者 J N B P


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

創建者 Saadullah A


Great introductory course for regression analysis and very practical indeed!

創建者 Rafał P


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

創建者 Sourabh S


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

創建者 Aditya S


Good to have deep insight into regression and various popular algorithm

創建者 Charles P


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

創建者 Patrick M d F


Excellent trad-off between theory, algorithims and practical examples

創建者 Nipun G


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

創建者 Andrej


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