The Dataset we are going to use is the Loan prediction dataset. The loan prediction dataset is a unique dataset that contains 12 columns. The data was gathered to predict if a customer is eligible for a loan. The Dataset is publicly available on Kaggle and can be accessed using this link. Let's Start with the bottom-up approach and build a simple Machine learning model.

Dialogflow is a powerful tool that allows us to create conversational tools without the complications of needing to handle natural language processing. But before we dive into the platform, it's important to understand all of the different concepts that tie together to create the conversational agents that we can create. When I started exploring the platform I jumped in without knowing what was what -- so in this article I want to quickly run through each of the concepts to help provide some foundational understanding for the platform. Just as you would say Hello to your friend before conversing with them, invoking an agent on the actions platform is carried out in the same way -- this kicks off the experience with our Agent in a conversational manner. At this point, this is the user requesting to speak to our agent -- this invocation is detected using the recognisable terms that we define in the Dialogflow console.