0

Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Deep Learning with TensorFlow 2 and Keras

You're reading from Deep Learning with TensorFlow 2 and Keras Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API

Product type Paperback

Published in Dec 2019

Publisher Packt

ISBN-13 9781838823412

Length 646 pages

Edition 2nd Edition

Languages

Python

Tools

Keras

Concepts

Deep Learning

Authors (3):

Dr. Amita Kapoor

Sujit Pal

Antonio Gulli

View More author details

Table of Contents (19) Chapters

Preface

1. Neural Network Foundations with TensorFlow 2.0

2. TensorFlow 1.x and 2.x FREE CHAPTER

3. Regression

4. Convolutional Neural Networks

5. Advanced Convolutional Neural Networks

6. Generative Adversarial Networks

7. Word Embeddings

8. Recurrent Neural Networks

9. Autoencoders

10. Unsupervised Learning

11. Reinforcement Learning

12. TensorFlow and Cloud

13. TensorFlow for Mobile and IoT and TensorFlow.js

14. An introduction to AutoML

15. The Math Behind Deep Learning

16. Tensor Processing Unit

17. Other Books You May Enjoy

18. Index

TensorFlow and Cloud

AI algorithms require extensive computing resources. With the availability of a large number of cloud platforms offering their services at competitive prices, cloud computing offers a cost-effective solution. In this chapter, we will talk about three main cloud platform providers that occupy the majority of the market share: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform. Moreover, once you have trained your model on cloud, you can use TensorFlow Extended (TFX) to move your model to production. The chapter will cover:

Creating and using virtual machines on cloud
Creating and training directly on Jupyter Notebook on cloud
Deploying the model on cloud
Using TFX for production
TensorFlow Enterprise

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 AU $24.99/month. Cancel anytime

Authors (3)

Antonio Gulli

Antonio Gulli

Antonio Gulli has a passion for establishing and managing global technological talent for innovation and execution. His core expertise is in cloud computing, deep learning, and search engines. Currently, Antonio works for Google in the Cloud Office of the CTO in Zurich, working on Search, Cloud Infra, Sovereignty, and Conversational AI.

See other products by Antonio Gulli

Amita Kapoor

Amita Kapoor

Amita Kapoor, a seasoned expert in Artificial Intelligence, serves as the Chief Artificial Intelligence Officer at TIPZ AI, bringing over 25 years of experience in AI, data science, and neuroscience. Her consultancy, NePeur, stands testament to her leadership in applying AI across diverse industries, enhancing operational efficiency and business intelligence. Amita is also a devoted board member of Neuromatch Academy, where she plays a crucial role in making neuroscience and deep learning education accessible to all. Holding a PhD from the University of Delhi, she has dedicated her career to education, authoring numerous articles and papers, and creating impactful online classes. Her significant contributions extend to pioneering projects in intelligent vehicle fleet management, home surveillance through AI-powered face detection, and robust data anonymization solutions. Connect with Amita on LinkedIn.

See other products by Amita Kapoor

Sujit Pal

Sujit Pal

Sujit Pal is a Technology Research Director at Elsevier Labs, an advanced technology group within the Reed-Elsevier Group of companies. His interests include semantic search, natural language processing, machine learning, and deep learning. At Elsevier, he has worked on several initiatives involving search quality measurement and improvement, image classification and duplicate detection, and annotation and ontology development for medical and scientific corpora.

See other products by Sujit Pal

Other recommended products

Related to this chapter

Deep Learning with Keras

Deep Learning with Keras

Keras is a high-level neural network library written in Python that runs on top of either Theano or TensorFlow. With this book, you'll learn the basics of Keras in a highly practical way and understand how this minimal, highly modular framework runs on both CPU and GPU, allowing you to put your ideas into action in the shortest possible time.

Apr 2017 10h 36m

Deep Learning with Keras

Deep Learning with Keras

Keras is a high-level neural network library written in Python that runs on top of either Theano or TensorFlow. With this book, you'll learn the basics of Keras in a highly practical way and understand how this minimal, highly modular framework runs on both CPU and GPU, allowing you to put your ideas into action in the shortest possible time.

Apr 2017 10h 36m

Deep Learning with Keras

Deep Learning with Keras

Keras is a high-level neural network library written in Python that runs on top of either Theano or TensorFlow. With this book, you'll learn the basics of Keras in a highly practical way and understand how this minimal, highly modular framework runs on both CPU and GPU, allowing you to put your ideas into action in the shortest possible time.

Apr 2017 10h 36m

Deep Learning with Keras

Deep Learning with Keras

Keras is a high-level neural network library written in Python that runs on top of either Theano or TensorFlow. With this book, you'll learn the basics of Keras in a highly practical way and understand how this minimal, highly modular framework runs on both CPU and GPU, allowing you to put your ideas into action in the shortest possible time.

Apr 2017 10h 36m

Deep Learning with Keras

Deep Learning with Keras

Keras is a high-level neural network library written in Python that runs on top of either Theano or TensorFlow. With this book, you'll learn the basics of Keras in a highly practical way and understand how this minimal, highly modular framework runs on both CPU and GPU, allowing you to put your ideas into action in the shortest possible time.

Apr 2017 10h 36m

Deep Learning with Keras

Deep Learning with Keras

Keras is a high-level neural network library written in Python that runs on top of either Theano or TensorFlow. With this book, you'll learn the basics of Keras in a highly practical way and understand how this minimal, highly modular framework runs on both CPU and GPU, allowing you to put your ideas into action in the shortest possible time.

Apr 2017 10h 36m

Deep Learning with Keras

Deep Learning with Keras

Keras is a high-level neural network library written in Python that runs on top of either Theano or TensorFlow. With this book, you'll learn the basics of Keras in a highly practical way and understand how this minimal, highly modular framework runs on both CPU and GPU, allowing you to put your ideas into action in the shortest possible time.

Apr 2017 10h 36m

Deep Learning with Keras

Deep Learning with Keras

Keras is a high-level neural network library written in Python that runs on top of either Theano or TensorFlow. With this book, you'll learn the basics of Keras in a highly practical way and understand how this minimal, highly modular framework runs on both CPU and GPU, allowing you to put your ideas into action in the shortest possible time.

Apr 2017 10h 36m

Deep Learning with Keras

Deep Learning with Keras

Keras is a high-level neural network library written in Python that runs on top of either Theano or TensorFlow. With this book, you'll learn the basics of Keras in a highly practical way and understand how this minimal, highly modular framework runs on both CPU and GPU, allowing you to put your ideas into action in the shortest possible time.

Apr 2017 10h 36m

Deep Learning with Keras

Deep Learning with Keras

Keras is a high-level neural network library written in Python that runs on top of either Theano or TensorFlow. With this book, you'll learn the basics of Keras in a highly practical way and understand how this minimal, highly modular framework runs on both CPU and GPU, allowing you to put your ideas into action in the shortest possible time.

Apr 2017 10h 36m

Deep Learning with Keras

Deep Learning with Keras

Keras is a high-level neural network library written in Python that runs on top of either Theano or TensorFlow. With this book, you'll learn the basics of Keras in a highly practical way and understand how this minimal, highly modular framework runs on both CPU and GPU, allowing you to put your ideas into action in the shortest possible time.

Apr 2017 10h 36m

Deep Learning with Keras

Deep Learning with Keras

Keras is a high-level neural network library written in Python that runs on top of either Theano or TensorFlow. With this book, you'll learn the basics of Keras in a highly practical way and understand how this minimal, highly modular framework runs on both CPU and GPU, allowing you to put your ideas into action in the shortest possible time.

Apr 2017 10h 36m

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