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

4.7
185 個評分
38 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.

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1 - Supervised Machine Learning: Regression 的 25 個評論(共 39 個)

創建者 Christopher W

2021年1月25日

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.

創建者 Nick V

2020年11月16日

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

創建者 Abdillah F

2020年11月7日

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

創建者 Minh L

2021年9月30日

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

創建者 Nir C

2021年10月8日

Great course! Covered everything I wished to learn!

創建者 Nancy C (

2021年4月24日

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.

創建者 michiel b

2021年2月15日

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.

創建者 Kalliope S

2021年6月24日

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.

創建者 Minhaj A A

2021年9月22日

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.

創建者 serkan m

2021年5月3日

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.

創建者 MAURICIO C

2021年3月25日

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

創建者 konutech

2020年12月13日

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

創建者 Nandana A

2020年12月28日

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

創建者 Ranjith P

2021年4月13日

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

創建者 Luis P S

2021年5月4日

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

創建者 Vivek O

2021年4月10日

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

創建者 Wissam Z

2021年6月6日

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

thank you

創建者 Saraswati P

2021年8月11日

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

創建者 Goh K L

2021年6月5日

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

創建者 Patrick B

2021年6月16日

Great way learn about machine learning development of regression models

創建者 Juan M

2021年6月11日

Very well structured course, the explanations were very clear.

創建者 My B

2021年4月14日

A well structured course with useful techniques in real life.

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!