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返回到 Supervised Machine Learning: Regression

学生对 IBM 提供的 Supervised Machine Learning: Regression 的评价和反馈

239 个评分
51 条评论


This course introduces you to one of the main types of modelling families of supervised Machine Learning: Regression. You will learn how to train regression models to predict continuous outcomes and how to use error metrics to compare across different models. This course also walks you through best practices, including train and test splits, and regularization techniques. By the end of this course you should be able to: Differentiate uses and applications of classification and regression in the context of supervised machine learning  Describe and use linear regression models Use a variety of error metrics to compare and select a linear regression model that best suits your data Articulate why regularization may help prevent overfitting Use regularization regressions: Ridge, LASSO, and Elastic net   Who should take this course? This course targets aspiring data scientists interested in acquiring hands-on experience  with Supervised Machine Learning Regression techniques in a business setting.   What skills should you have? To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Data Cleaning, Exploratory Data Analysis, Calculus, Linear Algebra, Probability, and Statistics....



Nov 15, 2020

Very well designed course, great that we could work with our own data and apply the theory. Looking forward to continue the journey.


Nov 6, 2020

Great course and very well structured. I'm really impressed with the instructor who give thorough walkthrough to the code.


26 - Supervised Machine Learning: Regression 的 50 个评论(共 54 个)

创建者 My B

Apr 14, 2021

A well structured course with useful techniques in real life.

创建者 Amir D

Feb 24, 2022

thanks for the great path learning DS-ML, great instructor

创建者 JV K

May 10, 2022

This is a comprehensive course. Learned a lot. Thank you!

创建者 Ana l D l

Jul 21, 2021

like that it uses math and also use programming

创建者 george s

Aug 20, 2021

Flawless course, everything was perfect!

创建者 Nikolas R W

Dec 24, 2020

Great course to learn about regression!

创建者 Alessandro S

Apr 15, 2021

Very well organized and explained.

创建者 Yohanes S

Apr 10, 2022

l loved the final projects !

创建者 Cui Y

Jan 14, 2022

Thank you!

创建者 Rorisang S

May 4, 2021


创建者 Abdur R K

Sep 16, 2021


创建者 Hariom K

Jan 23, 2022


创建者 Saeid S S

Apr 13, 2022


创建者 Volodymyr

Jul 15, 2021


创建者 Harshita B

Mar 29, 2022


创建者 Rohit p

Oct 18, 2021


创建者 Hossam G M

Jun 22, 2021

This course is very great. it focuses mainly on codes and how to get your models trained well with the best results. and for that a prior knowledge of the algorithms and the coding language in addition to the different libraries would be better.

创建者 Sid C

Mar 21, 2022

4/5 simply because not all the lesson Jupyter Notebooks are downloadable--the download links do not work. But the course content is very educational and has a good balance of difficulty enough to challenge you while learning.

创建者 Gianluca P

Jun 4, 2021

very clear contents and explanations. Regression methods are thoroughly explained. Examples of coding are indeed a very good basis to start coding on the project.


Feb 24, 2022

AN amazing course and contain really time values content only regret is that coursera doesn't come in dark mode

创建者 Pankaj Z

Apr 19, 2021

Very helpful course. There are few ups and downs but overall its helpful.

创建者 Mehdi S

Jan 20, 2021

Good course with nice exemple for illustration

创建者 Keyur U

Dec 24, 2020

A great course to kick start your ML journey.

创建者 Bernard F

Nov 27, 2020

An truly exciting course!

创建者 Iddi A A

Dec 11, 2020