Deep Learning in Production
Minimum price
Suggested price

Deep Learning in Production

About the Book

Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.

What you will learn?

  • Best practices to write Deep Learning code
  • How to unit test and debug Machine Learning code
  • How to build and deploy efficient data pipelines
  • How to serve Deep Learning models
  • How to deploy and scale your application
  • What is MLOps and how to build end-to-end pipelines

Who is this book for?

  • Software engineers who are starting out with deep learning
  • Machine learning researchers with limited software engineering background
  • Machine learning engineers who seek to strengthen their knowledge
  • Data scientists who want to productionize their models and build customer-facing applications

What tools you will use?

Tensorflow, Flask, uWSGI, Nginx, Docker, Kubernetes, Tensorflow Extended, Google Cloud, Vertex AI


Book description

Deep Learning research is advancing rapidly over the past years. Frameworks and libraries are constantly been developed and updated. However, we still lack standardized solutions on how to serve, deploy and scale Deep Learning models. Deep Learning infrastructure is not very mature yet.

This book accumulates a set of best practices and approaches on how to build robust and scalable machine learning applications. It covers the entire lifecycle from data processing and training to deployment and maintenance. It will help you understand how to transfer methodologies that are generally accepted and applied in the software community, into Deep Learning projects.

It's an excellent choice for researchers with a minimal software background, software engineers with little experience in machine learning, or aspiring machine learning engineers.

  • Share this book

  • Categories

    • Machine Learning
    • Google Cloud Platform
    • Artificial Intelligence
    • Software Architecture
    • Python
    • Docker
  • Feedback

    Email the Author(s)

About the Author

Sergios Karagiannakos
Sergios Karagiannakos

Sergios Karagiannakos is a Machine Learning Engineer with a focus on ML infrastructure and MLOps.

He has worked with several companies towards building and deploying Artificial Intelligence applications. During his last position in the ML infrastructure team at Hubspot, he helped build and maintain all Machine Learning services and pipelines inside the organization, serving more than 1 billion requests per day.

He graduated with a Master’s in Electrical and Computer Engineering from the University of Patras, and he then joined Eworx SA as a Data Scientist. Afterward, he worked as an independent ML engineer with small startups, and in 2019, he founded AI Summer, an educational platform around Deep Learning. During this time, he has authored more than 50 articles and published the Introduction to Deep Learning & Neural Networks course.

Interesting facts: He was included in the Top 100 influential voices and brands in Data Science and Deep Learning, he strives to bring the entire Greek tech community together, and he really wishes that Artificial General Intelligence will be solved in our lifetime.

Table of Contents



1. About this Book

1.1 Welcome to Deep Learning in Production

1.2 Is this book for me?

1.3 What is the book’s goal?

1.4 Will this be difficult to learn?

1.5 Why should you read this book?

1.6 How to use this book?

1.7 How is the book structured?

1.8 Do I need to know anything else before I get started?

2. Designing a Machine Learning System

2.1 Machine learning: phase zero

2.2 Data engineering

2.3 Model engineering

2.4 DevOps engineering

2.5 Putting it all together

2.6 Tackling a real-life problem

3. Setting up a Deep Learning Workstation

3.1 Laptop setup

3.2 Frameworks and libraries

3.3 Development tools

3.4 Python package and environment management

4. Writing and Structuring Deep Learning Code

4.1 Best practices

4.2 Unit testing

4.3 Debugging

5. Data Processing

5.1 ETL: Extract, Transform, Load

5.2 Data reading

5.3 Processing

5.4 Loading

5.5 Optimizing a data pipeline

6. Training

6.1 Building a trainer

6.2 Training in the cloud

6.3 Distributed training

7. Serving

7.1 Preparing the model

7.2 Creating a web application using Flask

7.3 Serving with uWSGI and Nginx

7.4 Serving with model servers

8. Deploying

8.1 Containerizing using Docker and Docker Compose

8.2 Deploying in a production environment

8.3 Continuous Integration and Delivery (CI / CD)

9. Scaling

9.1 A journey from 1 to millions of users

9.2 Growing with Kubernetes

10. Building an End-to-End Pipeline

10.1 MLOps

10.2 Building a pipeline using TFX

10.3 MLOps with Vertex AI and Google Cloud

10.4 More end-to-end solutions

11. Where to Go from Here


Table of Figures

About the Author

The Leanpub 60-day 100% Happiness Guarantee

Within 60 days of purchase you can get a 100% refund on any Leanpub purchase, in two clicks.

See full terms

80% Royalties. Earn $16 on a $20 book.

We pay 80% royalties. That's not a typo: you earn $16 on a $20 sale. If we sell 5000 non-refunded copies of your book or course for $20, you'll earn $80,000.

(Yes, some authors have already earned much more than that on Leanpub.)

In fact, authors have earnedover $12 millionwriting, publishing and selling on Leanpub.

Learn more about writing on Leanpub

Free Updates. DRM Free.

If you buy a Leanpub book, you get free updates for as long as the author updates the book! Many authors use Leanpub to publish their books in-progress, while they are writing them. All readers get free updates, regardless of when they bought the book or how much they paid (including free).

Most Leanpub books are available in PDF (for computers) and EPUB (for phones, tablets and Kindle). The formats that a book includes are shown at the top right corner of this page.

Finally, Leanpub books don't have any DRM copy-protection nonsense, so you can easily read them on any supported device.

Learn more about Leanpub's ebook formats and where to read them

Write and Publish on Leanpub

You can use Leanpub to easily write, publish and sell in-progress and completed ebooks and online courses!

Leanpub is a powerful platform for serious authors, combining a simple, elegant writing and publishing workflow with a store focused on selling in-progress ebooks.

Leanpub is a magical typewriter for authors: just write in plain text, and to publish your ebook, just click a button. (Or, if you are producing your ebook your own way, you can even upload your own PDF and/or EPUB files and then publish with one click!) It really is that easy.

Learn more about writing on Leanpub