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Intelligent Projects Using Python

You're reading from   Intelligent Projects Using Python 9 real-world AI projects leveraging machine learning and deep learning with TensorFlow and Keras

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781788996921
Length 342 pages
Edition 1st Edition
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Author (1):
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Santanu Pattanayak Santanu Pattanayak
Author Profile Icon Santanu Pattanayak
Santanu Pattanayak
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Table of Contents (12) Chapters Close

Preface 1. Foundations of Artificial Intelligence Based Systems FREE CHAPTER 2. Transfer Learning 3. Neural Machine Translation 4. Style Transfer in Fashion Industry using GANs 5. Video Captioning Application 6. The Intelligent Recommender System 7. Mobile App for Movie Review Sentiment Analysis 8. Conversational AI Chatbots for Customer Service 9. Autonomous Self-Driving Car Through Reinforcement Learning 10. CAPTCHA from a Deep-Learning Perspective 11. Other Books You May Enjoy

Customer support on Twitter

Now that we have some idea of how to build a chatbot using a recurrent neural network, we will build a chatbot using the customer service responses of 20 big brands to tweets posted by customers. The dataset twcs.zip can be located at https://www.kaggle.com/thoughtvector/customer-support-on-twitter. Each tweet is identified by the tweet_id and the tweet content is in the text field. The tweets posted by the customers can be identified by the in_response_to_tweet_id field. This should contain null values for customer tweets. For customer service tweets, this in_response_to_tweet_id field should point to the customer tweet_id to which this tweet is directed.

Creating data for training the chatbot

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