Mathematica 11 Machine Learning

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.

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