Inclusive ML >> How Google does Machine Learning
TOTAL POINTS 7
1.Which of the following are correct about Facets?
1 point
2.The things you incorrectly do not predict, things you exclude when instead it should have been included is called?
1 point
3.Which of the following help identify areas where a machine learning system could be more inclusive?
1 point
4.Which approach is followed to achieve a better performance across subgroups?
1 point
5.Which of the following are the parts of Facets?
1 point
6.The confusion matrix helps which of the following?
1 point
7.What do you call the things you incorrectly predicted, and the things you include that aren’t actually in the label and should have instead been excluded?
1 point
Related Questions & Answers:
- Introduction to ML on Google Cloud Introduction to ML on Google Cloud >> How Google does Machine Learning TOTAL POINTS 3 1.What is a common ... Read more...
- Introduction to AI First Introduction to AI First >> How Google does Machine Learning TOTAL POINTS 5 1.The main stages of Machine Learning ... Read more...
- Pre-trained ML APIs Pre-trained ML APIs >> How Google does Machine Learning TOTAL POINTS 5 1.Which of the following is NOT a ... Read more...
- All about data All about data >> How Google does Machine Learning TOTAL POINTS 5 1.What would you use to replace user ... Read more...
- Transform your business Transform your business >> How Google does Machine Learning TOTAL POINTS 3 1.Which of the following scenarios may require ... Read more...
- Python Notebooks in the Cloud Python Notebooks in the Cloud >> How Google does Machine Learning TOTAL POINTS 3 1.You are going to develop ... Read more...
