MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.
After 2 weeks, you will:
- Understand how to diagnose errors in a machine learning system, and
- Be able to prioritize the most promising directions for reducing error
- Understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance
- Know how to apply end-to-end learning, transfer learning, and multi-task learning
I've seen teams waste months or years through not understanding the principles taught in this course. I hope this two week course will save you months of time.
This is a standalone course, and you can take this so long as you have basic machine learning knowledge.
Course 3 of 5 in the Deep Learning Specialization.
Syllabus
WEEK 1
ML Strategy (1)
Streamline and optimize your ML production workflow by implementing strategic guidelines for goal-setting and applying human-level performance to help define key priorities.
WEEK 2
ML Strategy (2)
Develop time-saving error analysis procedures to evaluate the most worthwhile options to pursue and gain intuition for how to split your data and when to use multi-task, transfer, and end-to-end deep learning.
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.