How to Develop Competence With Deep Learning for Computer Vision
Last Updated on July 5, 2019
Computer vision is perhaps one area that has been most impacted by developments in deep learning.
It can be difficult to both develop and to demonstrate competence with deep learning for problems in the field of computer vision. It is not clear how to get started, what the most important techniques are, and the types of problems and projects that can best highlight the value that deep learning can bring to the field.
On approach is to systematically develop, and at the same time demonstrate competence with, data handling, modeling techniques, and application domains and present your results in a public portfolio of completed projects. This approach allows you to compound your skills from project to project. It also provides the basis for real projects that can be presented and discussed with prospective employers in order to demonstrate your capabilities.
In this post, you will discover how to develop and demonstrate competence in deep learning applied to problems in computer vision.
After reading this post, you will know:
- Developing a portfolio of completed small projects can both be leveraged on new projects in the future and demonstrate your competence with deep
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