Hands-On Machine Learning Courses

Practical Application of Machine Learning
The Basics

A 1-2 Day Course covering the basics of machine learning as applied to linear and networked assets:

  • Overview of Machine Learning as a Strategic Process

  • Data Preparation, Data Quality Assurance & Metrics

  • Statistical Analysis, Inferential Statistics

  • Hypothesis Testing, Confidence Intervals

  • Feature Analysis & Engineering, Genetic Algorithms

  • Math Fundamentals

  • Sampling Techniques, Cross-Validation, Learning Curves

  • Linear Regression, Bias-Variance Trade-Off, Validation & Performance

  • Supervised Classification Methods, Shallow Learning, Deep Learning

  • Classification Validation, Confusion Matrices, ROC Curves

  • Using the Process & Results to Mitigate Unwanted Events

  • Overview of Technology Options

  • Learning Resources

Practical Application of Machine Learning
Your Use Case

A 1-2 Day Course leveraging content from the Basics Course with application to your specific use case. This course allows attendees to put into practice machine learning fundamentals with their data using open source machine learning technology.