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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

Summary

Wow, that's an impressive set of practical examples of using deep learning projects in Python to build solutions in a creative space! Let's revisit the goals we set up for ourselves.

Defining the goal:
In this project, we're going to take the next step in our computational linguistics journey in deep learning projects in Python and generate new content for our client. We need to help them by providing a deep learning solution that generates new content that can be used in movie scripts, song lyrics, and music.

Deep learning generated content for creative purposes is obviously very tricky. Our realistic goal in this chapter was to demonstrate and train you on the skills and architecture needed to get started on these types of projects. Producing acceptable results takes interacting with the data, the model, and the outputs and testing it with the appropriate...

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