From the course: AI Foundations: Ideating and Prototyping
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Rapid prototyping and iterative testing
From the course: AI Foundations: Ideating and Prototyping
Rapid prototyping and iterative testing
- Imagine you are developing an AI tool to automate customer support. How can you ensure it's effective? The answer lies in rapid prototyping and iterative testing. Rather than striving for a perfect version upfront, this approach allows you to create, test, and refine early models. This way, you can adapt quickly based on what works and what doesn't. Your first prototype doesn't need to be complex. In fact, it's better if it isn't. For example, if you are building a chat bot, version 1 could simply respond to a few common questions. Use tools like TensorFlow or PyTorch to set up your initial model and platforms like Dialogflow to create basic dialogue structure for conversational AI. This lean prototype serves as your foundation for testing core functionality without wasting time on unnecessary features. Every iteration should have specific measurable objectives. Example goals. Achieve 80% accuracy in responding to basic queries. Reduce response time by 50%. Define these metrics…
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