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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：

526 - Machine Learning: Regression 的 550 个评论（共 1,001 个）

创建者 Sumit K

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May 5, 2020

I exprienced many good things in this course.

创建者 PRAVEEN R U

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Nov 21, 2018

Nice content with hands-on. Much recommended.

创建者 Lalithmohan S

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Mar 6, 2018

Fantastic content, so much to gain from this

创建者 Phuong N

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Aug 22, 2017

Great course! !!! Topics are well-explained.

创建者 Lin Y

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Mar 26, 2017

The best machine learning course on Coursera

创建者 Trinh N Q

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Jan 28, 2018

Give me a good understanding of Regression.

创建者 Pankaj K

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Mar 20, 2017

great explanation of the concepts involved!

创建者 clark.bourne

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Apr 20, 2016

Professional, comprehensive, worth to learn

创建者 Mathias L

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Mar 15, 2016

Very complete course and easy to understand

创建者 Mudambi S S

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Feb 10, 2016

The best course on Machine Learning so far!

创建者 Gustavo S

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Sep 11, 2020

Good trade-off between theory and practice

创建者 QZ Z

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Feb 18, 2017

Really can use in solving industry problem

创建者 THARANGINI S

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Jan 3, 2017

Excellent Fundamental course on Regression

创建者 Kazi N H

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Jan 13, 2016

One of awesome series of machine learning!

创建者 Bowen F

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Jul 19, 2020

feel really well when finish this course!

创建者 Xuening H

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Nov 30, 2019

So organized, so in depth, so much fun!!!

创建者 WEI Y

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Jul 5, 2018

Really great course! Highly recommend it!

创建者 Sal E

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Mar 21, 2018

I could give this course 6 out of 5 stars

创建者 Dongliang Z

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Feb 4, 2018

very good course! I enjoyed it very much.

创建者 Mai T

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Jun 26, 2016

Great content and very well instructions

创建者 Sean L

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Jun 25, 2016

a wonderful course about machine learning

创建者 James F

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Apr 27, 2016

One of the best courses I've ever taken.

创建者 Raul O

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Mar 25, 2016

Incredible course!

I totally recommend it

创建者 Bingnan L

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Dec 24, 2015

Very good, good practise! Good lectures!

创建者 fernandes m

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Oct 3, 2020

This was the most difficult I ever had.