Learn to use the artificial intelligence and neural network capabilities of Wolfram Language. Build a neural network using predefined layers. Use encoders and decoders for different classes of datasets. Train a neural network and measure its classification ability.
Summary
Learn about the properties of neural networks, their component layers, how to combine operations in a chain or graph container and how to train a network using the built-in functions of the Wolfram Language. See the use of encoders and decoders for automatically processing input and output to a network. Follow along step by step as we build a digit classifier from scratch, train a neural network and evaluate its performance.
Featured Products & Technologies: Wolfram Language (available in Mathematica and Wolfram|One)
You'll Learn To
Identify the basic building blocks of a neural network
Use encoders, decoders and various layers in a neural net
Make use of pre-trained networks in the Wolfram Neural Net Repository
Create and train a digit classifier and measure its accuracy
Summary
Learn about the properties of neural networks, their component layers, how to combine operations in a chain or graph container and how to train a network using the built-in functions of the Wolfram Language. See the use of encoders and decoders for automatically processing input and output to a network. Follow along step by step as we build a digit classifier from scratch, train a neural network and evaluate its performance.
Featured Products & Technologies: Wolfram Language (available in Mathematica and Wolfram|One)
You'll Learn To
Identify the basic building blocks of a neural network
Use encoders, decoders and various layers in a neural net
Make use of pre-trained networks in the Wolfram Neural Net Repository
Create and train a digit classifier and measure its accuracy
