3 Levels of Deep Learning Competence
Last Updated on August 19, 2019
Deep learning is not a magic bullet, but the techniques have shown to be highly effective in a large number of very challenging problem domains.
This means that there is a ton of demand by businesses for effective deep learning practitioners.
The problem is, how can the average business differentiate between good and bad practitioners?
As a deep learning practitioner, how can you best demonstrate that you can deliver skillful deep learning models?
In this post, you will discover the three levels of deep learning competence, and as a practitioner, what you must demonstrate at each level.
After reading this post, you will know:
- The problem of evaluating deep learning competence can best be addressed through project portfolios.
- A hierarchy of three competency levels can be used to sort practitioners and provide a framework for identifying the expected skills.
- The most common mistake that beginners make is starting at level 3, meaning they are trying to learn all levels at once, leading to confusion and frustration.
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