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A simple question-answering system built using IBM Watson's NLP services.

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Project: Bookworm

A simple question-answering system built using IBM Watson's NLP services.

Overview

In this project, I will use IBM Watson's NLP Services to create a simple question-answering system. I will first use the Discovery service to pre-process a document collection and extract relevant information. Then I will use the Conversation service to build a natural language interface that can respond to questions.

Getting Started

Clone this repository to your local computer.

If you have the AIND Anaconda environment prepared, now is a good time to activate it.

Open the notebook bookworm.ipynb from a terminal using the following command:

jupyter notebook bookworm.ipynb

Then follow the instructions in the notebook.

Note: You may have to install some packages (mentioned in the notebook). To do so, simply open another terminal and use pip.

Tasks

Complete each task in the notebook by implementing or modifying code wherever there is a TODO comment in a code cell, and answering any inline questions by modifying markdown cells. E.g.:

Q: What is the overall sentiment detected in this text? Mention the type (positive/negative) and score.

A: Negative, -0.798

Once you have completed all tasks, save the notebook, and then export it into a PDF or HTML. Remember to submit both the notebook (.ipynb) and the PDF/HTML, along with any other files that may be needed, e.g. data files, in case you use your own (sample files provided with the project don't need to be submitted).

Note: Please do not submit your service-credentials.json file - that is meant to be kept secret.

Extensions

Feel free to work on the project with your own dataset. You can also turn it into a web-based application and deploy it on Bluemix.

IBM Watson Resources

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. Please refer to Udacity Terms of Service for further information.

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