If you’ve getting familiar with the brave new world of machine learning, you’ve definitely come across the idea of training an inferencing. While these terms might appear similar on the surface, the actual difference is easy to spot.
In this video Thomas Henson uses the example of image recognition to show that training requires a massive dataset generally in a data center with a lot of compute and GPUs, while inferencing draws on a trained model to make a determination. The video goes into a little more detail, and does a great job getting you introduced to these concepts.
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