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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
5,474 個評分
1,016 條評論

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

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

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!

篩選依據:

976 - Machine Learning: Regression 的 983 個評論(共 983 個)

創建者 Konstantin K

2016年6月19日

I was not aible to complete this course for free. That was very disappointing! Universities like Stanford and John Hopkins find the opportunity to offer similar courses free of charge to peoople who want to learn. From University of Washington I have expected the same. Your bad!

Best regards

Konstantin

創建者 Ehsan M

2018年3月10日

The teachers have a great success in developing Tori, but, the teaching is not good. The way machine learning is presented is mixed, and all over the place.

Not worth to put time on

創建者 Om G

2020年8月14日

I saw the whole course.

I didn't get anything.

Maybe you can just increase some videos and explain neatly.

創建者 Andreas

2017年1月4日

This specialization is delayed for months now - very annoying! Don't give them money!

創建者 Adrien L

2017年2月2日

No good without the missing course and capstone projects

創建者 Mohamed H E E

2021年9月7日

Super outdated course, very hard to follow videos

創建者 Ken C

2017年2月4日

Not happy about course 5 & 6 got cancelled.

創建者 Deleted A

2021年5月4日

Why not have Python