Learn TensorFlow Enterprise: Build, manage, and scale machine learning workloads seamlessly using Google's TensorFlow Enterprise

Tung

$43.99

5 (7 Ratings)

Paperback Nov 2020 314 pages 1st Edition

Tung

$43.99

5 (7 Ratings)

Paperback Nov 2020 314 pages 1st Edition

What do you get with Print?

Instant access to your digital eBook copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

View table of contents

Preview Book

Download Code

Key benefits

Build scalable, seamless, and enterprise-ready cloud-based machine learning applications using TensorFlow Enterprise
Discover how to accelerate the machine learning development life cycle using enterprise-grade services
Manage Google’s cloud services to scale and optimize AI models in production

Description

TensorFlow as a machine learning (ML) library has matured into a production-ready ecosystem. This beginner’s book uses practical examples to enable you to build and deploy TensorFlow models using optimal settings that ensure long-term support without having to worry about library deprecation or being left behind when it comes to bug fixes or workarounds. The book begins by showing you how to refine your TensorFlow project and set it up for enterprise-level deployment. You’ll then learn how to choose a future-proof version of TensorFlow. As you advance, you’ll find out how to build and deploy models in a robust and stable environment by following recommended practices made available in TensorFlow Enterprise. This book also teaches you how to manage your services better and enhance the performance and reliability of your artificial intelligence (AI) applications. You’ll discover how to use various enterprise-ready services to accelerate your ML and AI workflows on Google Cloud Platform (GCP). Finally, you’ll scale your ML models and handle heavy workloads across CPUs, GPUs, and Cloud TPUs. By the end of this TensorFlow book, you’ll have learned the patterns needed for TensorFlow Enterprise model development, data pipelines, training, and deployment.

Who is this book for?

This book is for data scientists, machine learning developers or engineers, and cloud practitioners who want to learn and implement various services and features offered by TensorFlow Enterprise from scratch. Basic knowledge of the machine learning development process will be useful.

What you will learn

Discover how to set up a GCP TensorFlow Enterprise cloud instance and environment
Handle and format raw data that can be consumed by the TensorFlow model training process
Develop ML models and leverage prebuilt models using the TensorFlow Enterprise API
Use distributed training strategies and implement hyperparameter tuning to scale and improve your model training experiments
Scale the training process by using GPU and TPU clusters
Adopt the latest model optimization techniques and deployment methodologies to improve model efficiency

Estimated delivery fee Deliver to Russia

Economy delivery 10 - 13 business days

$6.95

Premium delivery 6 - 9 business days

$21.95

(Includes tracking information)

What do you get with Print?

Instant access to your digital eBook copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Frequently bought together

Mastering Reinforcement Learning with Python

$48.99

$43.99

Machine Learning for Algorithmic Trading

$57.99

Total $ 150.97

FAQs

What is the delivery time and cost of print book?

Shipping Details

USA:

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

Economy: Can deliver to P. O. Boxes and private residences.
Trackable service with delivery to addresses in Australia only.
Delivery time ranges from 7-9 business days for VIC and 8-10 business days for Interstate metro
Delivery time is up to 15 business days for remote areas of WA, NT & QLD.

Premium: Delivery to addresses in Australia only
Trackable delivery to most P. O. Boxes and private residences in Australia within 4-5 days based on the distance to a destination following dispatch.

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.

Unfortunately, due to several restrictions, we are unable to ship to the following countries:

Afghanistan
American Samoa
Belarus
Brunei Darussalam
Central African Republic
The Democratic Republic of Congo
Eritrea
Guinea-bissau
Iran
Lebanon
Libiya Arab Jamahriya
Somalia
Sudan
Russian Federation
Syrian Arab Republic
Ukraine
Venezuela

What is custom duty/charge?

Customs duty are charges levied on goods when they cross international borders. It is a tax that is imposed on imported goods. These duties are charged by special authorities and bodies created by local governments and are meant to protect local industries, economies, and businesses.

Do I have to pay customs charges for the print book order?

The orders shipped to the countries that are listed under EU27 will not bear custom charges. They are paid by Packt as part of the order.

List of EU27 countries: www.gov.uk/eu-eea:

A custom duty or localized taxes may be applicable on the shipment and would be charged by the recipient country outside of the EU27 which should be paid by the customer and these duties are not included in the shipping charges been charged on the order.

How do I know my custom duty charges?

The amount of duty payable varies greatly depending on the imported goods, the country of origin and several other factors like the total invoice amount or dimensions like weight, and other such criteria applicable in your country.

For example:

If you live in Mexico, and the declared value of your ordered items is over $ 50, for you to receive a package, you will have to pay additional import tax of 19% which will be $ 9.50 to the courier service.
Whereas if you live in Turkey, and the declared value of your ordered items is over € 22, for you to receive a package, you will have to pay additional import tax of 18% which will be € 3.96 to the courier service.

How can I cancel my order?

Cancellation Policy for Published Printed Books:

You can cancel any order within 1 hour of placing the order. Simply contact customercare@packt.com with your order details or payment transaction id. If your order has already started the shipment process, we will do our best to stop it. However, if it is already on the way to you then when you receive it, you can contact us at customercare@packt.com using the returns and refund process.

Please understand that Packt Publishing cannot provide refunds or cancel any order except for the cases described in our Return Policy (i.e. Packt Publishing agrees to replace your printed book because it arrives damaged or material defect in book), Packt Publishing will not accept returns.

What is your returns and refunds policy?

Return Policy:

We want you to be happy with your purchase from Packtpub.com. We will not hassle you with returning print books to us. If the print book you receive from us is incorrect, damaged, doesn't work or is unacceptably late, please contact Customer Relations Team on customercare@packt.com with the order number and issue details as explained below:

If you ordered (eBook, Video or Print Book) incorrectly or accidentally, please contact Customer Relations Team on customercare@packt.com within one hour of placing the order and we will replace/refund you the item cost.
Sadly, if your eBook or Video file is faulty or a fault occurs during the eBook or Video being made available to you, i.e. during download then you should contact Customer Relations Team within 14 days of purchase on customercare@packt.com who will be able to resolve this issue for you.
You will have a choice of replacement or refund of the problem items.(damaged, defective or incorrect)
Once Customer Care Team confirms that you will be refunded, you should receive the refund within 10 to 12 working days.
If you are only requesting a refund of one book from a multiple order, then we will refund you the appropriate single item.
Where the items were shipped under a free shipping offer, there will be no shipping costs to refund.

On the off chance your printed book arrives damaged, with book material defect, contact our Customer Relation Team on customercare@packt.com within 14 days of receipt of the book with appropriate evidence of damage and we will work with you to secure a replacement copy, if necessary. Please note that each printed book you order from us is individually made by Packt's professional book-printing partner which is on a print-on-demand basis.

What tax is charged?

Currently, no tax is charged on the purchase of any print book (subject to change based on the laws and regulations). A localized VAT fee is charged only to our European and UK customers on eBooks, Video and subscriptions that they buy. GST is charged to Indian customers for eBooks and video purchases.

What payment methods can I use?

You can pay with the following card types:

Visa Debit
Visa Credit
MasterCard
PayPal

What is the delivery time and cost of print books?

Shipping Details

USA:

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Unfortunately, due to several restrictions, we are unable to ship to the following countries:

Afghanistan
American Samoa
Belarus
Brunei Darussalam
Central African Republic
The Democratic Republic of Congo
Eritrea
Guinea-bissau
Iran
Lebanon
Libiya Arab Jamahriya
Somalia
Sudan
Russian Federation
Syrian Arab Republic
Ukraine
Venezuela

Filter reviews by

All

Amazon verified reviews

Kay T Mar 08, 2021

This book is unlike myriads of Tensorflow or machine learning books in the market. If you are interested in enterprise level use and deployment of Tensorflow models, this is the right book. This book helps me to go beyond the baby-steps of learning how to build Tensorflow ML models. All examples throughout this book uses either datasets or TFRecord data structure. I did not have a good understanding about these data structure before I bought and read this book. I often wonder why we need such data structures. After I read this book, I now understand that in an enterprise or production level, knowing how to handle distributed data is a must-have skill. I am glad that the author chose to use such enterprise-relevant data structures throughout the examples in this book. I would say this is a unique aspect of this book which differentiates it from other Tensorflow books. Another nice touch is that instead of teaching you how to build a ML model, it uses pre-built models Tensorflow Hub, and show me how to make it work for my own data. I learned transfer learning for the first time with book.To make most use of this book, it is important to clone the accompanying GitHub directory.For Tensorflow to be useful at enterprise level, it is important to have cloud integration. This book also helped me get started with learning how to use Google Cloud AI Platform with the integration to BigQuery data warehouse. Further, this book also contains step by step instructions on how to leverage cloud TPU and GPU to perform distributed training job. As a matter of fact, I now realize how important it is to use cloud TPU or GPU for time consuming job such as hyperparameter optimization. And the book shows me exactly how to do it. This book also did a very good job helping me learn how to different hyperparameter tuning methods work. I learned how hyperband algorithm works for the first time. That’s a delightful surprise.This book also describes how model optimization works, and why it is important. I didn’t realize that model size can be reduced by so much and yet retains similar or identical accuracy. Now I realize that once the model is built, optimization is always a good idea to make it more light-weight. And finally, when it comes to deployment, this book helped me understand how to serve the model behind a REST API using Tensorflow Serving. Model serving is a complicated issue in enterprise setting. This book helps me acquire the table stake knowledge about serving a model using Docker container. With the way described by this book, it turned out to be much easier than I thought.So overall, I would rate this book as a five-star book, and really appreciate the thoughts and works put in this book by the author. I definitely recommend it for anyone who has Tensorflow experience, and looking to take their skills to another level, which is much more relevant and practical for enterprise use. Well done.

Amazon Verified review

Christian P. Mar 09, 2021

Cloud computing is a relevant tool for companies to achieve their digital transformation, especially for those developing data-driven business models based on Deep Learning Frameworks as a core technology. Commence in cloud technologies can be overwhelming for beginners due to the tons of online tutorials, material, and documentation that are not always updated, creating frustration and delaying these technologies' adoption.The book is a useful guide and a great starting point for deploying the first AI-based applications for those who initiate Cloud Computing. Also, it is an excellent complementary material for those currently working as MLOps Engineers that want to understand advanced options in TensorFlow Enterprise and Google Cloud Computing. It includes sections with practical hands-on material easy to read and follow. Chapters handle relevant topics such as creating a data warehouse on the cloud, accessing the data efficiently using Tensorflow from different pythonic formats such as Pandas DataFrames or Numpy arrays, and small but valuable tips about using TPU instead of using a GPU. The hand-on material is available on Github, and such is a good source to start developing your ideas

laksh Apr 30, 2021

One single source of reference material for tensorflow. Practical guide.

Aishwary Feb 23, 2021

This book is a perfect introduction to TensorFlow, from learning basics to advanced features like model deployment in production. The best part about this book is sample code as a part of the explanation and images to illustrate the UI components on Google Cloud Platform. This book has an excellent use case to work google cloud AI notebooks while leveraging big data suite tools (tools like BigQuery). One of the other good things about this book is that it does not leave any concepts half explained. I liked the section on transfer learning and hyperparameter tuning (section 3 - chapter 4 and 6) the most. It also has details about working with TFRecords, which is an essential feature to work with data in the real world. Even if you do not work to deploy models in production, I would recommend every deep learning practitioner to read this book to get a perfect experience with all the concepts that one requires to leverage on a day-to-day basis.

SID ALLA Dec 14, 2020

I have been doing deep learning modeling using tensorflow programming for couple of years and its hard to actually build the model picking right number of GPU machines , setting them up properly, connecting data sources, buidl train models and then take the model to production. I have used the other public clouds but its much much easier on google cloud as they created Tensorflow in the first place. I also bought some beefy gaming machines with Nvidia chipsets but always had the ceremonial steps to do before i could do anything practical at cloud scale.This books explains clearly how to set up the sources in data warehouse, how to create notebooks, build models and deploy them without breaking the bank as its all taken care by Google Cloud.I have to point out the toughest parts of Deep Learning are the scaling using TPUs and GPUs and this book covers those aspects too. Not to underestimate, serving models are tricky and there are just too many options to do it. This book walks you through a good way to serve such models.Frankly this book saves time you will spend going through the many docs online and lets you quickly start from introduction and takes you to production.

Learn TensorFlow Enterprise: Build, manage, and scale machine learning workloads seamlessly using Google's TensorFlow Enterprise

What do you get with Print?