ML Strategy

Objectives

• Explain why Machine Learning strategy is important
• Apply satisficing and optimizing metrics to set up your goal for ML projects
• Choose a correct train/dev/test split of your dataset
• Define human-level performance
• Use human-level performance to define key priorities in ML projects

• Take the correct ML Strategic decision based on observations of performances and dataset

• Describe multi-task learning and transfer learning

• Recognize bias, variance and data-mismatch by looking at the performances of your algorithm on train/dev/test sets