Learn how to apply machine learning to your IoT data and gain a valuable advantage over your business competition. This course provides hands-on experience developing predictive maintenance and other ML solutions for IoT scenarios.
Are you ready to start using machine learning to develop a deeper understanding of your IoT data?
This course uses hands-on lab activities to guide students through a series of machine learning implementations that are common for IoT scenarios, such as predictive maintenance. After completing this course, students will be able to implement predictive analytics using their IoT data.
The course is divided into four modules that cover the following topic areas:
- Machine learning for IoT
- Data preparation techniques
- Predictive maintenance modeling
- Fault prediction modeling
What will you learn
- Describe machine learning scenarios and algorithms commonly pertinent to IoT
- Explain how to use the IoT solution Accelerator for Predictive Maintenance
- Prepare data for machine learning operations and analysis
- Apply feature engineering within the analysis process
- Choose the appropriate machine learning algorithms for given business scenarios
- Identify target variables based on the type of machine learning algorithm
- Train, evaluate, and apply various regression models
- Evaluate the effectiveness of regression models
- Apply deep learning to a predictive maintenance scenario