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In this wiki, we will explain how to use the Ovation framework to build components of a chatbot. For Ovation Summer Academy alpha (OSA-alpha) we have defined some tasks and business use-cases that the participating teams can choose from and work on during the course of the event. We have prepared these tasks such that they cover the scientific end of Conversational Intelligence (CI) and at the same time focus on realistic business scenarios that can make use of CI.

We looked at the profiles of the participants and saw that we have a mix of people who have a good experience in CI and some who know about existing solutions but do not have a hands-on experience. We believe that it will be a huge learning experience for all the participants no matter what their experience level is.

To give you a heads up, and a buffer to prepare for OSA-alpha we recommend you to already look into the following:

1. Tensorflow: We use Tensorflow as the ML/DL backbone of the Ovation framework. We have integrated version 1.2.0 f Tensorflow in Ovation and recommend you to at least go through the following tutorials,

        a. Getting Started

        b. Getting Started With TensorFlow

        c. MNIST For ML Beginners

        d. Deep MNIST for Experts

2. Rasa: To implement business use-cases, we will use Rasa. It is an open-source CI framework which helps you developing chatbots faster and the best part, for free. We are looking forward to building some demos in OSA alpha for the use-cases so we strongly recommend you to go through the following tutorial on integrating Rasa with Slack

        b. Training a Rasa bot: This will help you in developing the demos of the use-cases at OSA-alpha.

        b. Building a Slackbot with Rasa: This will help you in developing the demos of the use-cases at OSA-alpha.