One last piece of the puzzle is that, when dealing with neural networks, there are two major modes of operation: inference and training. Training is just what it sounds like—you give the neural network a large batch of data that represents a problem space, and let it chew through it, identifying things of interest and possibly learning to match them to labels you've provided along with the data. Inference, on the other hand, is using an already-trained neural network to give you answers in a problem space that it understands.
How to start experimenting with neural networks
Posted on Tuesday, December 10 2019 @ 11:34 CET by Thomas De MaesschalckYou may have heard a lot about neural networks and deep learning the last couple of years, but have you ever experimented with them yourself? If not, ARS Technica has an interesting article on how you can get started with your own neural nets. Within almost no time, you could be running your AI version of "Hello World" via the Google Colab platform.
