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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

EV

Jun 24, 2016

An in-depth overview of the regression techniques and models. I think it went as deep into the concepts as I wanted it to go. Being a developer I found it quite understandable, and useful.Keep it up!

PD

Mar 16, 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!

筛选依据：

501 - Machine Learning: Regression 的 525 个评论（共 1,001 个）

创建者 Jing

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Aug 14, 2017

A little bit boring and hard to focus on, sometimes

创建者 VANAJAKUMARI D

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May 6, 2024

very useful to improve my skills in new technology

创建者 Veer A S

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Mar 21, 2018

Excellent course to learn about Regression models.

创建者 Deleted A

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Aug 1, 2016

Lovely lectures with easy to follow up mathematics

创建者 Jesus B R F

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Aug 10, 2020

Excellent material and really clear presentations

创建者 Abhishek N S

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Apr 16, 2020

Emily fox is an great instructor for this course.

创建者 Adedeji A

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Feb 16, 2017

Excellent course, you'll get value for your money

创建者 Antonio C d S P

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Nov 13, 2016

Great ! I'm an IT guy learning a lot about math !

创建者 Manuel S

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Jun 18, 2016

Excellent!! A great option to be on the ML track

创建者 Giorgi G

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Dec 23, 2015

Very good course. I'd love to be course mentor :)

创建者 Eric H

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May 21, 2022

Great to know about Machine Learning: Regression

创建者 Smrithi P P

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May 28, 2020

This course was very useful to my future studies

创建者 Giampiero M

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Jun 14, 2019

great course, with more relevant technical infos

创建者 roopam k

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Jul 25, 2017

excellent course. good pace and good assignments

创建者 Tuhin S

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Sep 15, 2016

One of the best courses in Regression Modelling.

创建者 UMAR T

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Mar 12, 2020

Excellent machine learning course on regression

创建者 Nihar K

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Dec 26, 2019

It was very nice and great learning experience.

创建者 Oliver W

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Jul 19, 2016

Very tough course, but I enjoyed the challenge.

创建者 LIU Y

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Mar 22, 2016

best of the best, theoretically and practically

创建者 songwei

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Jan 15, 2016

cool, really great class about Regression model

创建者 Suyash C

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Jun 3, 2020

Courses like these make me want to live longer

创建者 Dat Q D

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Sep 28, 2017

Good course with balance theory and exercises.

创建者 Muhammad A

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Mar 31, 2017

Absolute loved the course. Highly recommended.

创建者 vamsi k

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Sep 21, 2016

very useful to understand the difficult topics

创建者 Rodolfo S

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Jun 7, 2016

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