Get started with machine learning in Mathematica 11. Learn how to separate training data from test data, prepare data for machine learning, perform supervised machine learning tasks, and more.
- [Curt] Hi, I'm Curt Frye. Welcome to Mathematica 11 Machine Learning. In this course, I'll show you how to get started with Machine Learning in Mathematica. I'll start by showing you how to split your data into training and test sets, and to import those files into Mathematica. Next, I'll show you how to manage your data, specifically how to standardize your data to avoid bias measurements, interpolate data to identify missing values, and to group or sort your data in meaningful ways.
Then, I'll show you how to perform linear regression, analyze time series data, and identify any known sequences or generating functions behind your data. Finally, I'll demonstrate how to separate data into classes, identify clusters, and assess your model's performance. I'm sure that you'll find that your time with Mathematica 11 Machine Learning will be time well spent. Dive right in.
- Separating training data from test data
- Importing data from a file
- Preparing data for machine learning
- Grouping and sorting elements using a rule
- Determining functions that generate data
- Finding a fit using a linear model
- Performing supervised learning tasks
- Classifying items using training data
- Identifying data clusters