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Deep Learning for Beginners

You're reading from   Deep Learning for Beginners A beginner's guide to getting up and running with deep learning from scratch using Python

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Product type Paperback
Published in Sep 2020
Publisher Packt
ISBN-13 9781838640859
Length 432 pages
Edition 1st Edition
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Authors (2):
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Pablo Rivas Pablo Rivas
Author Profile Icon Pablo Rivas
Pablo Rivas
Dr. Pablo Rivas Dr. Pablo Rivas
Author Profile Icon Dr. Pablo Rivas
Dr. Pablo Rivas
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Toc

Table of Contents (20) Chapters Close

Preface 1. Section 1: Getting Up to Speed
2. Introduction to Machine Learning FREE CHAPTER 3. Setup and Introduction to Deep Learning Frameworks 4. Preparing Data 5. Learning from Data 6. Training a Single Neuron 7. Training Multiple Layers of Neurons 8. Section 2: Unsupervised Deep Learning
9. Autoencoders 10. Deep Autoencoders 11. Variational Autoencoders 12. Restricted Boltzmann Machines 13. Section 3: Supervised Deep Learning
14. Deep and Wide Neural Networks 15. Convolutional Neural Networks 16. Recurrent Neural Networks 17. Generative Adversarial Networks 18. Final Remarks on the Future of Deep Learning 19. Other Books You May Enjoy

Questions and answers

  1. Does Colab run on my personal computer?

No, it runs in the cloud, but with some skill and setup, you could connect it to your own personal cloud.

  1. Does Keras use GPUs?

Yes. Since Keras runs on TensorFlow (in the setup of this book) and TensorFlow uses GPUs, then Keras also does.

  1. What are the two main coding paradigms in Keras?

(A) Sequential model; (B) Functional API.

  1. Why do we care about Dopamine?

Because there are only a few reinforcement learning frameworks you can trust out there, and Dopamine is one of them.

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