Deep learning is not like any other technology, but it is in many cases the only technology that can solve certain problems. We need to ensure that all people involved in the project have a common understanding of what is required, how the process works, and that we have a realistic view of what is possible with the tools at hand. To boil down all this to its core components we could consider a few important rules:
create a common ground of understanding, this will ensure the right mindset
state early how progress should be measured
communicate clearly how different machine learning concepts works
acknowledge and consider the inherited uncertainty, it is part of the process
In order to define AI, we must first define the concept of intelligence in general. A paraphrased definition based on Wikipedia is:
Intelligence can be generally described as the ability to perceive information and retain it as knowledge to be applied towards adaptive behaviors within an environment or context.
While there are many different definitions of intelligence, they all essentially involve learning, understanding, and the application of the knowledge learned to achieve one or more goals.
In this course, we are going to work on the following projects.
Pan Card Tempering Detector (Heruko)
Dog breed prediction (Streamlit)
Image Watermarking (Heruko)
Traffic Sign Classification
Text extraction (Streamlit)