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Python Deep Learning Projects

You're reading from   Python Deep Learning Projects 9 projects demystifying neural network and deep learning models for building intelligent systems

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781788997096
Length 472 pages
Edition 1st Edition
Languages
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Authors (3):
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Rahul Kumar Rahul Kumar
Author Profile Icon Rahul Kumar
Rahul Kumar
Matthew Lamons Matthew Lamons
Author Profile Icon Matthew Lamons
Matthew Lamons
Abhishek Nagaraja Abhishek Nagaraja
Author Profile Icon Abhishek Nagaraja
Abhishek Nagaraja
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Toc

Table of Contents (17) Chapters Close

Preface 1. Building Deep Learning Environments FREE CHAPTER 2. Training NN for Prediction Using Regression 3. Word Representation Using word2vec 4. Building an NLP Pipeline for Building Chatbots 5. Sequence-to-Sequence Models for Building Chatbots 6. Generative Language Model for Content Creation 7. Building Speech Recognition with DeepSpeech2 8. Handwritten Digits Classification Using ConvNets 9. Object Detection Using OpenCV and TensorFlow 10. Building Face Recognition Using FaceNet 11. Automated Image Captioning 12. Pose Estimation on 3D models Using ConvNets 13. Image Translation Using GANs for Style Transfer 14. Develop an Autonomous Agent with Deep R Learning 15. Summary and Next Steps in Your Deep Learning Career 16. Other Books You May Enjoy

Sequence-to-Sequence Models for Building Chatbots

We're learning a lot and doing some valuable work! In the evolution of our hypothetical business use case, this chapter builds directly on Chapter 4, Building an NLP Pipeline for Building Chatbots, where we created our Natural Language Processing (NLP) pipeline. The skills we learned so far in computational linguistics should give us the confidence to expand past the training examples in this book and tackle this next project. We're going to build a more advanced chatbot for our hypothetical restaurant chain to automate the process of fielding call-in orders.

This requirement would mean that we'd have to combine a number of technologies that we've learned so far. But for this project, we'll be interested in learning how to make a chatbot that is more contextually aware and robust, so that we could integrate...

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