Introduction to Neural Networks in Wolfram Language

  • Instructor Led
  • 2 h 30 min
  • Intermediate
  • 1 Certification

Course Overview

Requirements: This course requires basic working knowledge of Wolfram Language.

Featured Products & Technologies: Wolfram Language (available in Mathematica and Wolfram|One)

Outline

  • What Is a Neural Network: Get introduced to the concepts of neural net architecture and deep learning, as well as the high-level overview of what neural nets are doing.
  • Building Blocks of the Neural Net Framework: Learn about the building blocks of neural networks available within the Wolfram Neural Net Framework. Learn about how data is represented, encoders and decoders, built-in layers and the tools available for training and testing networks.
  • Explore Examples: Explore image, audio, video and natural language processing. Practical examples include a neural network to recognize handwritten digits from their images.
  • The Neural Net Repository: Take a quick tour of the repository, a public collection of neural networks, from which models can be retrieved and reused with little effort. See a simple example of using transfer learning to adapt and retrain the pre-built Wolfram ImageIdentify net model for the specific use case of determining dog breed from an image.

Schedule

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Certifications Available

  • Completion Certificate

    Certify your completion of this course by attending an online class and passing the quiz.