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Ayushman Dash edited this page Sep 12, 2017 · 15 revisions

Introduction

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 Conversational Intelligence.

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. The following sections will explain how to prepare for OSA-alpha and what are the contents of this wiki.

How to prepare for OSA-alpha

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.

Contents

  1. [Tasks]: Tasks descriptions and how to address them.

  2. [Ovation by Example]: An example of how to use the Ovation framework and its various modules

  3. [Components of Ovation]: Description of all the components of Ovation

  4. [Using the Datasets API]: How to use the Datasets API and build models faster

  5. [Build your own Model]: How to create your own model using Ovation

  6. [Using the Template Models]: How to use existing templates to write your own model in minutes

  7. [Voice Interface]: How to use the Ovation voice interface to build a voice based bot

  8. [Tools and Utilities]: How to use some tools and utility scripts that Ovation provides

  9. [Contribution Guidelines]: How to contribute to the Ovation framework

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