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Building Applications with the Neural Network Repository
Tuseeta Banerjee and Matteo Salvarezza
Learn how to build applications with models from the Wolfram Neural Net Repository and get an overview of some of the newest models available for classification, feature extraction, image processing, speech, audio and more. See applications by students from Wolfram summer programs and observe real-time examples of model training with data. A final real-world example applies computer vision tasks to digital pathology for the purposes of cancer diagnosis.
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Channels: Virtual Events
701 videos match your search.
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This event features demos and tutorials using Wolfram technologies for 2D and 3D image analysis and computer vision. Wolfram's integrated workflow combines high level image processing and machine learning in ... |
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Learn about the highly automated machine learning framework in the Wolfram Language, including task-oriented functions that can process numeric data, text, images and more. Examples include image search and classification, ... |
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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 ... |
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Learn about recurrent neural nets and why they are interesting. Find out how you can work with recurrent nets using the neural network framework in the Wolfram Language. See a ... |
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