You have worked on this project for a year and you finally achieve: 

- Human-level performance: 0.10%
- Training set error: 0.05%
- Dev set error: 0.05%

Human Level Performance: After more work on the previous model, what can you conclude?

You have also evaluated your model on the test set, and find the following:

- Human-level performance: 0.1%
- Training set error: 2.0%
- Dev set error: 2.1%
- Test set error: 7.0%

University of Michigan - Ann Arbor

Google

You define 0.1% as “human-level performance.” After working further on your algorithm, you end up with the following: 

- Human-level performance: 0.1%
- Training set error: 2.0%
- Dev set error: 2.1%

Human Level Performance: Based on the evidence below, which two of the following four options seem the most promising to try? 

Machine Learning Yearning, a free ebook from Andrew Ng, teaches you how to structure Machine Learning projects.
https://www.deeplearning.ai/machine-learning-yearning/

Note: The content of the book is aligned with the Coursera Deeplearning.ai specialization.  https://www.deeplearning.ai/deep-learning-specialization/ 

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