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Avis et commentaires pour d'étudiants pour Supervised Machine Learning: Regression par IBM

4.7
étoiles
185 évaluations
38 avis

À propos du cours

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....

Meilleurs avis

NV
15 nov. 2020

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

AF
6 nov. 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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1 - 25 sur 39 Avis pour Supervised Machine Learning: Regression

par Christopher W

25 janv. 2021

Really good course but it is whistle-stop through the methods. I strongly recommend getting a book to accompany the course if you are relatively new just so you can cross reference some of the methods and functions.

I found some of the examples a little more difficult to apply to the course work because of how they were demonstrated in the lab. This is NOT a bad thing, all good learning, but when you're trying to unpack things it's good to have another reference source handy.

par Nick V

16 nov. 2020

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

par Abdillah F

7 nov. 2020

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

par Minh L

30 sept. 2021

very detailed. However, it is better if the gradient decent has its lesson.

par Nir C

8 oct. 2021

Great course! Covered everything I wished to learn!

par Nancy C (

24 avr. 2021

Before taking this course, I tested similar courses offered by other institutes or universities. I am glad that I chose IBM because it has a good balance of concepts and applications. I learned a lot from this course. and will be using what I learned in analyzing experimental and survey data.

I gave this course a 4 instead of 5 because there was insufficient explanation on the different evaluation metrics.

par michiel b

15 févr. 2021

Good overview of the different regression models and the theory behind them. Could be a bit more attention to common pittfalls and type and size of problems which are usually addressed by these methods.

par Kalliope S

24 juin 2021

T​he balance between theory and application is such that both are left quite poorly covered. One does not get an understanding of how algorithms work, explanations focus on 'intuititve' understanding. At the same time, the coding part is not particularly detailed, either. Moreover, there are several mistakes in videos, quizzes and jupyter lab books. I would not recommend this course.

par Minhaj A A

22 sept. 2021

The course covered various aspects of regression modelling in good detail and the practice notebooks were also very helpful in implementing and reinforcing the learnings of course. Though the subject matter is quite wide, efforts were made by the instructor to cover most of them.

par serkan m

3 mai 2021

Thanks very much for this great course. It is comprehensive and intuitive in terms of Regression analysis. It covers all the necessary tools for an essential and sufficient application of Regression analysis.

par MAURICIO C

25 mars 2021

It was an exceedingly difficult for me, sometimes JSON files under Jupiter Notebook links made me freeze. But this intensity of challenge brings me an improvement for my skills.

Thanks Coursera & IBM

par konutech

13 déc. 2020

The instructor from videos is amazing. Great tutor. So far the courses from IBM Machine Learning Professional Certificate are really, really good.

par Nandana A

28 déc. 2020

Learned really about supervised learning and more importantly regularization and some available methods.

par Ranjith P

13 avr. 2021

I recommend this course to everyone who wants to excel in Machine Learning. This is a Great Course!

par Luis P S

4 mai 2021

Excellent!!! I rather recommend the course for those who need to understand properly and fast!

par Vivek O

10 avr. 2021

Very well presented. This is without doubt the best series for Machine Learning on Coursera.

par Wissam Z

6 juin 2021

best course ever I learned regression and polynomials in a professional way.

thank you

par Saraswati P

11 août 2021

Well structured course. Concepts are explained clearly with hands on exercises.

par Goh K L

5 juin 2021

Please give the lecturer credit and include him as one of the instructors

par Patrick B

16 juin 2021

Great way learn about machine learning development of regression models

par Juan M

11 juin 2021

Very well structured course, the explanations were very clear.

par My B

14 avr. 2021

A well structured course with useful techniques in real life.

par Ana l D l

21 juil. 2021

like that it uses math and also use programming

par george s

20 août 2021

Flawless course, everything was perfect!

par Nikolas R W

24 déc. 2020

Great course to learn about regression!