Today is a freaking cool day. Why do you ask? Because today I am writing an article on how to use two of the coolest freaking big data/data science tools out there together to do epic shit! Lets start with HBase. HBase is a way to have a big data solution with query performance at an interactive level. So many folks are starting to just dump data into HBase. In the project teddy solution, we are dumping tweets, dialogue and dialogue annotations to power our open domain conversational api. There really is no other way that is easy to use for us to do this.
The second part of project teddy is to predict based on an incoming conversational component, what sort of response the speaker is attempting to illicit from the teddy bear. If we power our teddy bear with predictive analytics and big data, this would be perfect. What better platform to do this quickly and easily than AzureML?
Welcome to Part 2! We will be discussing Binary Classification. So I hope many of you have started using AzureML. If not, you should definitely check it out. Here is the link to the dev center for it. This article series will focus on a few key points.
Understanding the Evaluation of each Model Type.
Understanding the published Web Service of each Model
If you are looking for how to build a simple how to get started, check out this article.
The series will be broken down into a three parts.