AI Tools for Modeling and Prediction

Define blending and stacking techniques

Identify scenarios where blending improves outcomes

Implement a simple blending or stacking approach

Understand performance metrics for predictive models

Evaluate models using different assessment metrics

Determine the suitability of metrics for specific types of data

Describe the anatomy of neural networks.

Explain the concept of activation functions.

Identify various neural network architectures.

Identify the importance of hyperparameter tuning

Implement grid and random search methods

Evaluate model performance through cross-validation techniques