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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

Product type Paperback

Published in Sep 2020

Publisher Packt

ISBN-13 9781838640859

Length 432 pages

Edition 1st Edition

Languages

Python

Tools

Keras

Concepts

Deep Learning

Authors (2):

Pablo Rivas

Dr. Pablo Rivas

View More author details

Table of Contents (20) Chapters

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

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Other deep learning libraries

Besides the big two, TensorFlow and Keras, there are other competitors that are making their way in the world of deep learning. We already discussed PyTorch, but there are more. Here we talk about them briefly.

Caffe

Caffe is also a popular framework developed at UC Berkeley (Jia, Y., et.al. 2014). It became very popular in 2015-2016. A few employers still demand this skillset and scholarly articles still mention its usage. However, its usage is in decay in part due to the major success of TF and the accessibility of Keras.

For more information about Caffe, visit: https://caffe.berkeleyvision.org.

Note also the existence of Caffe2, which is developed by Facebook and is open source. It was built based on Caffe, but now Facebook has its new champion, PyTorch.

Theano

Theano was developed by Yoshua Bengio's group at the University of Montreal in 2007 (Al-Rfou, R., et.al. 2016). Theano has a relatively old user base that probably saw the rise of TF. The...

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Authors (2)

Rivas

Rivas

Dr. Pablo Rivas is an assistant professor of computer science at Baylor University in Texas. He worked in industry for a decade as a software engineer before becoming an academic. He is a senior member of the IEEE, ACM, and SIAM. He was formerly at NASA Goddard Space Flight Center performing research. He is an ally of women in technology, a deep learning evangelist, machine learning ethicist, and a proponent of the democratization of machine learning and artificial intelligence in general. He teaches machine learning and deep learning. Dr. Rivas is a published author and all his papers are related to machine learning, computer vision, and machine learning ethics. Dr. Rivas prefers Vim to Emacs and spaces to tabs.

See other products by Rivas

Pablo Rivas

Pablo Rivas

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