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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

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

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!

筛选依据：

576 - Machine Learning: Regression 的 600 个评论（共 1,001 个）

创建者 Alexander S

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Feb 7, 2016

great, learning curve increasing.

创建者 Jenhau C

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Mar 30, 2019

Great course! Very good insight!

创建者 Fernando B

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Feb 21, 2017

Best Course on ML yet on the Web

创建者 Matic D B

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Feb 9, 2016

Great and representative course.

创建者 Sukwon O

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Dec 5, 2020

Learned a lot from this course.

创建者 DEEP K S

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Aug 30, 2020

can you guys upgrade to python3

创建者 Muhammad Z H

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Aug 29, 2019

Thanks Professor, I learnt alot

创建者 Kunal T

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Dec 19, 2018

Extremely well designed course.

创建者 Sanjay M

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Jun 24, 2017

Excellent foundational course .

创建者 yuanfan p

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Jun 18, 2017

Concise. Hope for more content.

创建者 tonghong c

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Jun 14, 2017

Best ML course I've ever taken!

创建者 易灿

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Nov 27, 2016

课程很生动，讲的也很详细！如果能提供些相关算法的资料就更好了！

创建者 Kanstantsin H (

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Feb 8, 2016

It's cool! I love your courses!

创建者 Kim K L

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Jan 3, 2016

Great course ... learned a lot!

创建者 Brian N

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May 19, 2018

Good to learn again this topic

创建者 prabal k

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Aug 23, 2017

Very good flow of the content.

创建者 Lionel T L

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Apr 15, 2017

complete, explicite, rich code

创建者 Shiva R

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Nov 20, 2016

Concepts explained in detailed

创建者 童哲明

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Jun 12, 2016

Kernel regression还是有许多不太清楚的地方！

创建者 Radomir N

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Feb 21, 2016

Very nice and engaging course!

创建者 Katalin S

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Jan 30, 2016

Exceptionally well done course

创建者 Nicolas T

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Dec 18, 2015

Best Machine learning mooc !!!

创建者 Israel d S R d A

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Feb 18, 2020

Great course very recommended

创建者 Harsh C

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Oct 17, 2019

Teaches me lots of new things

创建者 Lanqing B

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Sep 26, 2017

Well structured and designed.