Introduction to Machine Learning with KNIME
Offered By: LinkedIn Learning
Course Description
Overview
Learn KNIME, a popular open-source platform for predictive analytics and machine learning. Discover how to use KNIME for merging and aggregation, modeling, data scoring, and more.
Syllabus
Introduction
- Open-source machine learning with KNIME
- Who is this course for?
- Why use an Analytics Workbench?
- Using CRISP-DM to evaluate tools
- Why choose KNIME?
- The KNIME interface
- Find case studies on the Examples Server
- The KNIME Hub
- Add thousands of nodes with Extensions
- Search and Help
- Accessing data
- File reader node
- Database access with KNIME
- Describe data and verify data quality
- Explore data: Scatterplot
- Explore data: Boxplot
- Merging with the Joiner node
- Aggregating with the GroupBy node
- Creating new variables with Construct
- Select data with Column Filter
- Balancing data with Row Sampling node
- Clean data with the Missing Value node
- Format with Cell Splitter
- KNIME modeling options
- Regression example
- Decision tree
- Decision tree: Scoring new data
- Components in KNIME: AutoML and XAI
- PMML
- R and GGPLOT2
- Python options in KNIME
- Certification in KNIME
- Next steps
Taught by
Keith McCormick
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