Machine Learning for Robotics Training Course
This course introduces machine learning methods in robotics applications for government.
It provides a broad overview of existing methods, motivations, and main ideas in the context of pattern recognition.
After a brief theoretical background, participants will perform simple exercises using open-source software (such as R) or other popular tools.
This course is available as onsite live training in US Government or online live training.Course Outline
- Regression
- Probabilistic Graphical Models for government applications
- Boosting techniques for government data analysis
- Kernel Methods for enhanced predictive modeling in government
- Gaussian Processes for robust statistical inference in government
- Evaluation and Model Selection for government projects
- Sampling Methods for efficient data collection in government
- Clustering algorithms for government data segmentation
- Conditional Random Fields (CRFs) for government data modeling
- Random Forests for improved decision-making in government
- Informative Vector Machines (IVMs) for advanced government analytics
Requirements
Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.
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