Structuring Machine Learning Projects

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This is the third course of total five courses for obtaining "Deep Learning Specialization" on "Coursera" platform by Andrew Ng which is provided by "deeplearning.ai".


This course explains how to build a successful machine learning project. This course also has two "flight simulators" that let the students practice decision-making as a machine learning project leader. This provides industry experience.

This course explain the low level concept of:

  1. Understanding of diagnosing errors in a machine learning system.
  2. Prioritizing the most promising directions for reducing error.
  3. Understanding of complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance. 
  4. Applying end-to-end learning, transfer learning, and multi-task learning.

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1 comments

  1. Cool you write, the information is very good and interesting, I'll give you a link to my site. Andrew Chunis

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