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.
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Structuring Machine Learning Projects
This course is part of Deep Learning Specialization
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Instructors: Andrew Ng
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2 assignments
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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
Instructors
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Reviewed on Jul 25, 2018
Very important and valuable intuitions about DNN training/optimization. It's full of really practical information while implementing my own models.DNN을 실제 적용할때 반드시 이해하고 적용해야 할 실질적 내용들로 구성된 멋진 코스 입니다!
Reviewed on Sep 21, 2018
This is a must course in the entire specialization. It covers the step by step procedure to approach and solve a problem. The case studies provided are real world problems which are so much helpful.
Reviewed on Oct 15, 2018
The course is very teaching in my uneducated opinion and will help m later in life, hopefully.I wish the test question had been more coherent.I enjoyed learning it, and the simulator is a great idea!
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