Model Training
Explore how to train AI models effectively by focusing on data accessibility and variety, tuning hyperparameters iteratively, and ensuring model performance meets defined benchmarks. Understand the importance of real-world data for creating robust AI products ready for market.
We'll cover the following...
Assessment of model
In this lesson, we will explore the standard process for gathering data to train a model and tune hyperparameters optimally to achieve a certain level of performance and optimization. In the implementation phase—step four of the NPD process—we’re looking for a level of performance that would be considered optimal based on the define phase—step two of the NPD process—before we move to the next phase of marketing and crafting our message for what success looks like when using our product. A lot has to happen in the implementation phase before we can do that.