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Learn to use the state-of-the-art neural net framework in Wolfram Language. Find pre-built and pre-trained models in the Wolfram Neural Net Repository and see how to adapt them to your own applications.
This course provides an introduction to the state-of-the-art Neural Net Framework in Wolfram Language. You will learn how to explore the Wolfram Neural Net Repository for pre-built and pre-trained models and how to apply them to your own dataset. Also see how you can use transfer learning to adapt models for your own applications. The course will then discuss the building blocks of neural nets, along with instructions for putting them together within a symbolic framework to build your own neural network. Simple examples of training and testing a neural network will be discussed, along with options to inspect output from hidden layers of the net. This course is part of the series Exploring AI Foundations with Wolfram Tools.
This course provides an introduction to the state-of-the-art Neural Net Framework in Wolfram Language. You will learn how to explore the Wolfram Neural Net Repository for pre-built and pre-trained models and how to apply them to your own dataset. Also see how you can use transfer learning to adapt models for your own applications. The course will then discuss the building blocks of neural nets, along with instructions for putting them together within a symbolic framework to build your own neural network. Simple examples of training and testing a neural network will be discussed, along with options to inspect output from hidden layers of the net. This course is part of the series Exploring AI Foundations with Wolfram Tools.
