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LinkedIn Learning

Mathematica 11 Machine Learning

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Get started with machine learning. Learn how to separate training data from test data, prepare data for machine learning, perform supervised machine learning tasks, and more.

Syllabus

Introduction
  • Welcome
  • What you should know
  • Exercise files
1. Introducing Machine Learning
  • Overview of machine learning tasks
  • Separate training data from test data
  • Import data from a file
2. Preparing Data for Machine Learning
  • Standardize (normalize) or rescale data
  • Replace values near zero with zero
  • Interpolate data to enter missing values
  • Count values by adherence or non-adherence to a rule
  • Group elements using a rule
  • Sort elements using a rule
3. Determining Functions that Generate Data
  • Find a fit using a linear model
  • Find a time series that fits given data
  • Find a formula that represents a data set
  • Find a function that generates a given sequence of values
4. Performing Supervised Learning Tasks
  • Calculate the logistic sigmoid function for a data set
  • Classify items using training data
  • Predict values using training data
  • Measure classifier function performance
  • Measure predictor function performance
  • Identify data clusters
Conclusion
  • Next steps

Taught by

Curt Frye

Reviews

4.3 rating at LinkedIn Learning based on 21 ratings

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