AWS w/ C# #

Publisher: O’Reilly #

Release Date: 2022 #

Working with O’Reilly and AWS to write a book on building solutions on AWS with C#/.NET 6.

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Practical MLOps #

Publisher: O’Reilly #

Release Date: Early 2021 #

mlops-color

Abstract #

Getting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models.

Current and aspiring machine learning engineers–or anyone familiar with data science and Python–will build a foundation in MLOps tools and methods (along with AutoML and monitoring and logging), then learn how to implement them in AWS, Microsoft Azure, and Google Cloud. The faster you deliver a machine learning system that works, the faster you can focus on the business problems you’re trying to crack. This book gives you a head start.

You’ll discover how to:

Apply DevOps best practices to machine learning
Build production machine learning systems and maintain them
Monitor, instrument, load-test, and operationalize machine learning systems
Choose the correct MLOps tools for a given machine learning task
Run machine learning models on a variety of platforms and devices, including mobile phones and specialized hardware

Cloud Computing for Data Analysis #

A practical guide to Data Science, Machine Learning Engineering and Data Engineering #

Publisher: Pragmatic AI Labs #

Release Date: (Early 2021) #

Cloud Computing for Data Analysis

Abstract #

This book is designed to give you a comprehensive view of cloud computing including Big Data and Machine Learning. A variety of learning resources will be used including interactive labs on Cloud Platforms (Google, AWS, Azure) using Python. This is a project-based book with extensive hands-on assignments.

Read Chapters Online #

Additional Resources #

Video #

Cloud Computing with Python #

Source Code #

Cloud Computing with Python Source Code

Minimal Python #

Publisher: Pragmatic AI Labs #

Release Date: 2020 #

Minimal Python

Abstract #

Even books that have “learn” in the title introduce readers to hopelessly complex topics like object-oriented programming or concurrency. It turns out YAGNI (You Ain’t Gonna Need It). Why teach students topics they won’t use either ever, or not for a few years?

Read Chapters Online #

Additional Resources #

Video #

Learn Python in One Hour #

Source Code #

Minimal Python Book Source Code

Python Command Line Tools: Design powerful apps with Click #

Publisher: Pragmatic AI Labs #

Release Date: 2020 #

Python Command Line Tools

Abstract #

Learn the ultimate interface…the command-line.

Read Chapters Online #

Additional Resources #

Source Code #

Python Command Line Tools Book Source Code

Testing in Python #

Publisher: Pragmatic AI Labs #

Release Date: 2020 #

Testing in Python

Abstract #

Getting started with testing can be hard, and this book aims make it all very easy by using examples and straightforwardly explaining the process. Testing is a core principle of robust software implementations and should be a prime skill to master that can be applied to any project.

Read Chapters Online #

Chapter01: Configuring The Environment

Additional Resources #

Video #

Advanced Testing in Python #

Source Code #

Testing in Python Book Source Code

Python For DevOps: Learn Ruthlessly Effective Automation #

Publisher: O’Reilly Media #

Release Date: December 31st, 2019 #

Python for Unix and Linux System Administration

Abstract #

Much has changed in technology over the past decade. Data is hot, the cloud is ubiquitous, and many organizations need some form of automation. Throughout these transformations, Python has become one of the most popular languages in the world. This practical resource shows you how to use Python for everyday Linux systems administration tasks with today’s most useful DevOps tools, including Docker, Kubernetes, and Terraform.

Learning how to interact and automate with Linux is essential for millions of professionals. Python makes it much easier. With this book, you’ll learn how to develop software and solve problems using containers, as well as how to monitor, instrument, load-test, and operationalize your software. Looking for effective ways to “get stuff done” in Python? This is your guide.

Python foundations, including a brief introduction to the language How to automate text, write command-line tools, and automate the filesystem Linux utilities, package management, build systems, monitoring and instrumentation, and automated testing Cloud computing, infrastructure as code, Kubernetes, and serverless Machine learning operations and data engineering from a DevOps perspective Building, deploying, and operationalizing a machine learning project

Pragmatic AI: An Introduction to Cloud-based Machine Learning #

Publisher: O’Reilly Media #

Release Date: December 31st, 2019 #

Pragmatic AI: An Introduction to Cloud-based Machine Learning

Abstract #

Pragmatic AI will help you solve real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Noah Gift demystifies all the concepts and tools you need to get results—even if you don’t have a strong background in math or data science. Gift illuminates powerful off-the-shelf cloud offerings from Amazon, Google, and Microsoft, and demonstrates proven techniques using the Python data science ecosystem. His workflows and examples help you streamline and simplify every step, from deployment to production, and build exceptionally scalable solutions. As you learn how machine language (ML) solutions work, you’ll gain a more intuitive understanding of what you can achieve with them and how to maximize their value. Building on these fundamentals, you’ll walk step-by-step through building cloud-based AI/ML applications to address realistic issues in sports marketing, project management, product pricing, real estate, and beyond. Whether you’re a business professional, decision-maker, student, or programmer, Gift’s expert guidance and wide-ranging case studies will prepare you to solve data science problems in virtually any environment.

Python for Unix and Linux System Administration #

Publisher: O’Reilly Media #

Release Date: June 2009 #

Python for Unix and Linux System Administration

Python is an ideal language for solving problems, especially in Linux and Unix networks. With this pragmatic book, administrators can review various tasks that often occur in the management of these systems, and learn how Python can provide a more efficient and less painful way to handle them.

Each chapter in Python for Unix and Linux System Administration presents a particular administrative issue, such as concurrency or data backup, and presents Python solutions through hands-on examples. Once you finish this book, you’ll be able to develop your own set of command-line utilities with Python to tackle a wide range of problems. Discover how this language can help you:

Read text files and extract information
Run tasks concurrently using the threading and forking options
Get information from one process to another using network facilities
Create clickable GUIs to handle large and complex utilities
Monitor large clusters of machines by interacting with SNMP programmatically
Master the IPython Interactive Python shell to replace or augment Bash, Korn, or Z-Shell
Integrate Cloud Computing into your infrastructure, and learn to write a Google App Engine Application
Solve unique data backup challenges with customized scripts
Interact with MySQL, SQLite, Oracle, Postgres,and SQLAlchemy

With this book, you’ll learn how to package and deploy your Python applications and libraries, and write code that runs equally well on multiple Unix platforms. You’ll also learn about several Python-related technologies that will make your life much easier.