Introduction to Machine Learning 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 Machine Learning?: Learn about common machine learning terms. See examples of built-in Wolfram Language functions that can perform a variety of machine learning tasks. Explore common paradigms of machine learning as well as their variations.
  • Machine Learning Workflows: Learn about traditional machine learning workflows where you get data and then build, train, test and deploy a model. Also get a peek at newer workflows that incorporate LLMs (large language models).
  • Supervised Learning: Understand how one of the most popular machine learning paradigms works. Use Wolfram Language superfunctions Classify and Predict with labeled data. Handle common issues with training data.
  • Unsupervised Learning: Use unsupervised learning to work with unlabeled data. Use Wolfram Language functions like FeatureExtract, FindClusters and ClusterClassify. Detect anomalies in data and model the distribution of non-anomalous data.

Schedule

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Certifications Available

  • Completion Certificate

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