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Voltar para Supervised Machine Learning: Regression

Comentários e feedback de alunos de Supervised Machine Learning: Regression da instituição IBM

250 classificações
51 avaliações

Sobre o curso

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....

Melhores avaliações


15 de nov de 2020

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


6 de nov de 2020

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

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26 — 50 de 54 Avaliações para o Supervised Machine Learning: Regression

por My B

14 de abr de 2021

A well structured course with useful techniques in real life.

por Amir D

24 de fev de 2022

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

por JV K

10 de mai de 2022

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

por Ana l D l

21 de jul de 2021

like that it uses math and also use programming

por george s

20 de ago de 2021

Flawless course, everything was perfect!

por Nikolas R W

24 de dez de 2020

Great course to learn about regression!

por Alessandro S

15 de abr de 2021

Very well organized and explained.

por Yohanes S

10 de abr de 2022

l loved the final projects !

por Cui Y

14 de jan de 2022

Thank you!

por Rorisang S

4 de mai de 2021


por Abdur R K

16 de set de 2021


por Hariom K

23 de jan de 2022


por Saeid S S

13 de abr de 2022


por Volodymyr

15 de jul de 2021


por Harshita B

29 de mar de 2022


por Rohit p

18 de out de 2021


por Hossam G M

22 de jun de 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.

por Sid C

21 de mar de 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.

por Gianluca P

4 de jun de 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.


24 de fev de 2022

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

por Pankaj Z

19 de abr de 2021

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

por Mehdi S

20 de jan de 2021

Good course with nice exemple for illustration

por Keyur U

24 de dez de 2020

A great course to kick start your ML journey.

por Bernard F

27 de nov de 2020

An truly exciting course!

por Iddi A A

11 de dez de 2020