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學生對 IBM 提供的 Supervised Machine Learning: Regression 的評價和反饋

4.7
250 個評分
51 條評論

課程概述

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....

熱門審閱

NV

2020年11月15日

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

AF

2020年11月6日

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

篩選依據:

26 - Supervised Machine Learning: Regression 的 50 個評論(共 54 個)

創建者 My B

2021年4月14日

A well structured course with useful techniques in real life.

創建者 Amir D

2022年2月24日

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

創建者 JV K

2022年5月10日

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

創建者 Ana l D l

2021年7月21日

like that it uses math and also use programming

創建者 george s

2021年8月20日

Flawless course, everything was perfect!

創建者 Nikolas R W

2020年12月24日

Great course to learn about regression!

創建者 Alessandro S

2021年4月15日

Very well organized and explained.

創建者 Yohanes S

2022年4月10日

l loved the final projects !

創建者 Cui Y

2022年1月14日

Thank you!

創建者 Rorisang S

2021年5月4日

Excellent!

創建者 Abdur R K

2021年9月16日

excellent

創建者 Hariom K

2022年1月23日

Thanks

創建者 Saeid S S

2022年4月13日

great

創建者 Volodymyr

2021年7月15日

Super

創建者 Harshita B

2022年3月29日

Good

創建者 Rohit p

2021年10月18日

best

創建者 Hossam G M

2021年6月22日

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.

創建者 Sid C

2022年3月21日

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.

創建者 Gianluca P

2021年6月4日

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.

創建者 BATTLE K

2022年2月24日

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

創建者 Pankaj Z

2021年4月19日

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

創建者 Mehdi S

2021年1月20日

Good course with nice exemple for illustration

創建者 Keyur U

2020年12月24日

A great course to kick start your ML journey.

創建者 Bernard F

2020年11月27日

An truly exciting course!

創建者 Iddi A A

2020年12月11日

Excellent