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Regression Analysis with Yellowbrick(으)로 돌아가기

Coursera Project Network의 Regression Analysis with Yellowbrick 학습자 리뷰 및 피드백

77개의 평가
16개의 리뷰

강좌 소개

Welcome to this project-based course on Regression Analysis with Yellowbrick. In this project, we will build a machine learning model to predict the compressive strength of high performance concrete (HPC). Although, we will use linear regression, the emphasis of this project will be on using visualization techniques to steer our machine learning workflow. Visualization plays a crucial role throughout the analytical process. It is indispensable for any effective analysis, model selection, and evaluation. This project will make use of a diagnostic platform called Yellowbrick. It allows data scientists and machine learning practitioners to visualize the entire model selection process to steer towards better, more explainable models.Yellowbrick hosts several datasets from the UCI Machine Learning Repository. We’ll be working with the concrete dataset that is well suited for regression tasks. The dataset contains 1030 instances and 8 real valued attributes with a continuous target. We we will cover the following topics in our machine learning workflow: exploratory data analysis (EDA), feature and target analysis, regression modelling, cross-validation, model evaluation, and hyperparamter tuning. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, Yellowbrick, and scikit-learn pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

최상위 리뷰

필터링 기준:

Regression Analysis with Yellowbrick의 16개 리뷰 중 1~16

교육 기관: Raul G

2020년 6월 25일

This course could have been way better! The tutor tells you what the code does but does not explain why we use of what the plots actually mean. you just get a ball park educated guess about what to do with the plots. the rhyme environment is laggy and unresponsive at times and it is not due to my internet connection as i have tested this in 2 different geographical locations. what this course does is shows you lots of cool graphs and you get a VERY basic sort of explanation about the graph. not worth the money as I can get a way better course on Udemy for the same money!

교육 기관: Lorenço

2020년 7월 11일

Excellent code and theory balance. Not too long nor too short. I wish the author could provide a PDF with all the concepts and theories compilation around the most important ideas. Congratulations. Cheers!

교육 기관: Saurabh K

2020년 5월 12일

Great Instructor.

Good Platform for Learning as well as Practice side by side.

Thank you for sharing your knowledge.

교육 기관: Manish W

2020년 5월 2일

the instructor need to include more theory

교육 기관: Chanreaksa C

2020년 9월 14일

Great guide project, it is easy to follow

교육 기관: Rajkumar R

2020년 10월 23일

Good Experience. New things learnt

교육 기관: Arnab S

2020년 9월 8일

Nice way to learn new things.

교육 기관: Dr. P R

2020년 5월 15일

Very interesting

교육 기관: Jack C

2020년 6월 3일

Great project!

교육 기관: SHRUTI S

2020년 5월 14일

Nice course

교육 기관: Dr. J R P

2020년 5월 7일


교육 기관: p s

2020년 6월 24일


교육 기관: Vajinepalli s s

2020년 6월 20일


교육 기관: THAKOR R R

2020년 5월 22일


교육 기관: tf

2021년 7월 5일

G​ood introduction to Yellowbrick. The audio is not as good as other projects.

교육 기관: Ammar S

2020년 7월 13일

Nice and a very good project to do in week-end.