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学生对 University of Washington 提供的 Machine Learning: Regression 的评价和反馈

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5,581 个评分

课程概述

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....

热门审阅

AM

Apr 25, 2020

Very informative, practical course with excellent instructors, I would recommend this course to anyone doing basic machine learning. The only issue I see is that the course can be offered in R.

KM

May 4, 2020

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

筛选依据：

476 - Machine Learning: Regression 的 500 个评论（共 1,001 个）

创建者 Andrew V G

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Jan 25, 2018

good level of rigor and the notebooks were very well done

创建者 g

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Aug 28, 2016

Intuitive and very helpful, great assignment not too hard

创建者 Nilesh K

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Jul 18, 2016

very good coverage of a wide range of topics. impressive!

创建者 Taylor N

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Jan 10, 2016

I really learned a lot about going above and beyond OLS.

创建者 Mariano

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Mar 24, 2020

very hard and challeging course. learn a lot of topics.

创建者 Liu S

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Nov 7, 2017

easy to learn! assignments are just at the right level!

创建者 How T

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Oct 23, 2020

Lots of practical information. Assignments are great.

创建者 zhengqian z

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Feb 1, 2017

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

创建者 Sudip C

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May 3, 2016

Very detailed, Liked optional sections also. Loved it.

创建者 Christopher G

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Apr 9, 2016

One of the best courses I've taken in Machine Learning

创建者 Antonio P L

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Dec 30, 2015

Fantastic course and really complete about regression.

创建者 Enrique D

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May 26, 2017

Excellent course, challenging but very good learning!

创建者 Bayu W

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Jan 17, 2016

Excellent course, learned a lot of valuable concepts.

创建者 Tomasz J

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Jan 6, 2016

Excellent in depth dive into Regression! Great profs!

创建者 Dip A

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Jul 13, 2020

THIS COURSE IS BEST TO LEARN ABOUT LINEAR REGRESSION

创建者 Ankit

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Apr 9, 2020

MORE THAN ENOUGH TO KNOW ABOUT REGRESSION.

THANK YOU.

创建者 Simon C

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Apr 6, 2020

This is a great course about regression for novices.

创建者 Jack :

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Sep 24, 2017

Very in depth for someone looking to go into detail.

创建者 sharecj

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May 13, 2017

The best machine learning course I have ever joined!

创建者 fan c

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Apr 25, 2017

useful and easy to understand. Teacher is very nice.

创建者 Shan-Jyun W

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Jul 3, 2016

Great teaching, great materials, and a great course!

创建者 shahreyar

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Jun 19, 2020

Pretty amazing course! Had a lot of fun doing this.

创建者 Le H N

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Jun 29, 2018

I gain many knowledge from this course . Excellent.