0

Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

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

Leave a review - let other readers know what you think

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...

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at $19.99/month. Cancel anytime

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

See other products by Pablo Rivas

Other recommended products

Related to this chapter

Machine Learning for Healthcare Analytics Projects

Machine Learning for Healthcare Analytics Projects

Machine Learning in the healthcare domain is booming because of its abilities to provide accurate and stabilized techniques. This book is packed with new methodologies to create efficient solutions for healthcare analytics. We will build five end-to-end projects to evaluate the efficiency of AI apps to carry out simple-to-complex healthcare analytics tasks.

Oct 2018 4h 28m

Machine Learning for Healthcare Analytics Projects

Machine Learning for Healthcare Analytics Projects

Machine Learning in the healthcare domain is booming because of its abilities to provide accurate and stabilized techniques. This book is packed with new methodologies to create efficient solutions for healthcare analytics. We will build five end-to-end projects to evaluate the efficiency of AI apps to carry out simple-to-complex healthcare analytics tasks.

Oct 2018 4h 28m

Machine Learning for Healthcare Analytics Projects

Machine Learning for Healthcare Analytics Projects

Machine Learning in the healthcare domain is booming because of its abilities to provide accurate and stabilized techniques. This book is packed with new methodologies to create efficient solutions for healthcare analytics. We will build five end-to-end projects to evaluate the efficiency of AI apps to carry out simple-to-complex healthcare analytics tasks.

Oct 2018 4h 28m

Machine Learning for Healthcare Analytics Projects

Machine Learning for Healthcare Analytics Projects

Machine Learning in the healthcare domain is booming because of its abilities to provide accurate and stabilized techniques. This book is packed with new methodologies to create efficient solutions for healthcare analytics. We will build five end-to-end projects to evaluate the efficiency of AI apps to carry out simple-to-complex healthcare analytics tasks.

Oct 2018 4h 28m

Deep Learning with Hadoop

Deep Learning with Hadoop

Feb 2017 6h 52m

Deep Learning with Hadoop

Deep Learning with Hadoop

Feb 2017 6h 52m

Deep Learning with Hadoop

Deep Learning with Hadoop

Feb 2017 6h 52m

Deep Learning with Hadoop

Deep Learning with Hadoop

Feb 2017 6h 52m

Deep Learning with Hadoop

Deep Learning with Hadoop

Feb 2017 6h 52m

Hands-On Deep Learning Algorithms with Python

Hands-On Deep Learning Algorithms with Python

This book introduces basic-to-advanced deep learning algorithms used in a production environment by AI researchers and principal data scientists; it explains algorithms intuitively, including the underlying math, and shows how to implement them using popular Python-based deep learning libraries such as TensorFlow.

Jul 2019 17h 4m

Hands-On Deep Learning Algorithms with Python

Hands-On Deep Learning Algorithms with Python

This book introduces basic-to-advanced deep learning algorithms used in a production environment by AI researchers and principal data scientists; it explains algorithms intuitively, including the underlying math, and shows how to implement them using popular Python-based deep learning libraries such as TensorFlow.

Jul 2019 17h 4m

Hands-On Deep Learning Algorithms with Python

Hands-On Deep Learning Algorithms with Python

This book introduces basic-to-advanced deep learning algorithms used in a production environment by AI researchers and principal data scientists; it explains algorithms intuitively, including the underlying math, and shows how to implement them using popular Python-based deep learning libraries such as TensorFlow.

Jul 2019 17h 4m

Personalised recommendations for you

Based on your interests and search pattern

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m