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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 2. Training NN for Prediction Using Regression FREE CHAPTER 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

Building an NLP Pipeline for Building Chatbots

Our project has expanded once again, thanks to the good work that we've been doing. We started off working for a restaurant chain, helping them to classify handwritten digits for use in a text notification system, used to alert their waiting guests that their table was ready. Based on this success, and when the owners realized that their customers were actually responding to the texts, we were asked to contribute a deep learning solution using Natural Language Processing (NLP) to accurately classify text into a meaningful sentiment category that would give the owners an indication as to their satisfaction with the dining experience.

Do you know what happens to deep learning engineers that do good work? They get asked to do more!

This project for the next business use case is pretty cool. What we're being asked to do is to...

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