Evaluate business performance of algorithmic models
About
This unit is about evaluating the performance of deployed algorithmic models at meeting expected business outcomes
Scope
define performance metrics, perform analysis on model performance
Define performance metrics
- identify the objective being addressed by the model
- define suitable evaluation criteria and metrics to evaluate model performance as per objective
Perform analysis on model performance
- evaluate the performance of the algorithmic models
- identify the hyperparameters to maximize model performance
- test different hyperparameter configurations
- use best-fit hyperparameter configurations to maximize model performance
Required Knowledge & Understanding
Technical Skills
- different performance metrics to monitor business outcomes of algorithmic models
- different methodological approaches for identifying model hyperparameters such as grid search, random search, bayesian optimization
- how to tune hyperparameter configurations
- how to identify and refer anomalies in data
- how to work on various operating systems such as linux, ubuntu, or windows
Soft Skills
Analytical Thinking
impact analysis of the various actions performed and disseminating relevant information to others
Attention to Detail
check your work is complete and free from errors