How to construct feed-forward networks with Wolfram Language. Properties of artificial intelligence and neural networks are explored using real-world data and image classification examples.
Summary
The Wolfram Language neural network framework provides symbolic building blocks to build, train and tune a network as well as automatically process input and output using encoders and decoders. Learn how to do this in steps, along with examples of logistic regression and basic image recognition.
Featured Products & Technologies: Wolfram Language (available in Mathematica and Wolfram|One)
You'll Learn To
Convert different data types to tensors
Use class encoders and decoders
Work with different types of layers and connect the layers
Specify loss layers
Perform logistic classification using real-world data
Train convolutional neural networks
Summary
The Wolfram Language neural network framework provides symbolic building blocks to build, train and tune a network as well as automatically process input and output using encoders and decoders. Learn how to do this in steps, along with examples of logistic regression and basic image recognition.
Featured Products & Technologies: Wolfram Language (available in Mathematica and Wolfram|One)
You'll Learn To
Convert different data types to tensors
Use class encoders and decoders
Work with different types of layers and connect the layers
Specify loss layers
Perform logistic classification using real-world data
Train convolutional neural networks
