Retour à Visual Machine Learning with Yellowbrick
Avis et commentaires pour d'étudiants pour Visual Machine Learning with Yellowbrick par Coursera Project Network
71 évaluations
À propos du cours
Welcome to this project-based course on Visual Machine Learning with Yellowbrick. In this course, we will explore how to evaluate the performance of a random forest classifier on the Poker Hand data set using visual diagnostic tools from Yellowbrick. With an emphasis on visual steering of our analysis, we will cover the following topics in our machine learning workflow: feature analysis, feature importance, algorithm selection, model evaluation using regression, cross-validation, and hyperparameter 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.
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1 - 11 sur 11 Avis pour Visual Machine Learning with Yellowbrick
par Khandaker M A
•8 août 2020
This is a better-planned guided project with practice quizzes which really helps. So I would definitely like to recommend this course for those who wants to have a knowledge on visual machine learning.
par Ramya G R
•10 juin 2020
I really enjoyed this project. Thank you very much for your valuable teaching. Like to learn more from your end.
par Abhishek C
•10 mai 2020
but the cloud desktop is not good
par Gangone R
•2 juil. 2020
very useful course
par MUHAMMED S S A
•16 avr. 2020
It's very useful
par Kamlesh C
•26 juil. 2020
Thanks
par tale p
•28 juin 2020
good
par p s
•26 juin 2020
Nice
par sarithanakkala
•24 juin 2020
Good
par Maxwell S d C
•15 juin 2020
Nice but short and somwhat lacking theory
par Sujal V
•18 mars 2020
good
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