In the third course of the Deep Learning Specialization, you will learn how to build a successful machine learning project and get to practice decision-making as a machine learning project leader.


Structuring Machine Learning Projects
This course is part of Deep Learning Specialization



Instructors: Andrew Ng
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There are 2 modules in this course
Streamline and optimize your ML production workflow by implementing strategic guidelines for goal-setting and applying human-level performance to help define key priorities.
What's included
13 videos3 readings1 assignment
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.
What's included
11 videos2 readings1 assignment
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Reviewed on Mar 31, 2020
It is very nice to have a very experienced deep learning practitioner showing you the "magic" of making DNN works. That is usually passed from Professor to graduate student, but is available here now.
Reviewed on Jul 26, 2018
Very important and valuable intuitions about DNN training/optimization. It's full of really practical information while implementing my own models.DNN鞚 鞁れ牅 鞝侅毄頃犽晫 氚橂摐鞁 鞚错暣頃橁碃 鞝侅毄頃挫暭 頃 鞁れ鞝 雮挫毄霌る 甑劚霅 氅嬱 旖旍姢 鞛呺媹雼!
Reviewed on Aug 20, 2021
Very helpful tips for navigating possible problems that would likely occur while building/training a model. The "pilot-training" exercieses, that mimick real-life problems / projects, are excellent !
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