Pragmatic AI: An Introduction to Cloud-Based Machine Learning

678 Pages·2018·24.8 MB·English

by  Noah Gift

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Praise for Pragmatic AI
“[This is] a sweeping guide that bridges the gap between the promise of AI and
solutions to the gritty problems that must be solved to deploy real-world
projects. Clear and usable, Pragmatic AI covers much more than just Python and
AI algorithms.”
–Christopher Brousseau, founder and CEO of Surface Owl, the Enterprise AI
platform
“A fantastic addition for any technology enthusiast! There is so much you can
say about this book! Noah Gift really made this a practical guide for anyone
involved with machine learning in the industry. Not only does it explain how one
can apply machine learning on large data sets, it provides a valuable perspective
on technology feedback loops. This book will benefit many data science and
development teams so they can create and maintain their applications efficiently
right from the beginning.”
–Nivas Durairaj, technical account manager, AWS (Certified Professional
Architect AWS)
“A great read if you want insights into building production-quality ML pipelines
and tools that truly help your data engineering, data science, or data DevOps
team. Even experienced developers often find themselves spinning their wheels
on low-productivity tasks. Oftentimes, software books and university classes
don't explain the steps needed to go into production. Noah has a gift for finding
pragmatic approaches to software deployments that can really accelerate the
development and delivery process. He has a focus and passion for enabling rapid
software solutions that is very unique.
“The key to building production-quality ML pipelines is automation. Tasks and
steps, which engineers may do manually during the research or prototype phase,
must be automated and scaled in order to create a production system. This book
is full of practical and fun exercises that will help any Python developer
automate and extend their pipelines into the cloud.
“I'm currently working with big data, ML pipelines, Python, AWS, Google
cloud, and Azure at Roofstock.com, an online real estate company. Our analytics
database is approaching 500 million rows! Within this book I found many
practical tips and exercises that will immediately improve my own productivity.
Recommended!”
–Michael Vierling, lead engineer, Roofstock
Pragmatic AI
An Introduction to Cloud-Based Machine
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ISBN-13: 978-0-13-486386-3
ISBN-10: 0-13-486386-0
1 18
This book is dedicated to my family
and extended family, who have always been there for me: my wife, Leah Gift;
my mom, Shari Gift; my son, Liam Gift; and my mentor,
Dr. Joseph Bogen
Contents
Preface
Acknowledgments
About the Author
I: Introduction to Pragmatic AI
1 Introduction to Pragmatic AI
Functional Introduction to Python
Procedural Statements
Printing
Create Variable and Use Variable
Multiple Procedural Statements
Adding Numbers
Adding Phrases
Complex Statements
Strings and String Formatting
Adding and Subtracting Numbers
Multiplication with Decimals
Using Exponents
Converting Between Different Numerical Types
Rounding Numbers
Data Structures
Dictionaries
Lists
Functions
Using Control Structures in Python
for Loops
While Loops
If/Else
Intermediate Topics
Final Thoughts
2 AI and ML Toolchain
Python Data Science Ecosystem: IPython, Pandas, NumPy, Jupyter
Notebook, Sklearn
R, RStudio, Shiny, and ggplot
Spreadsheets: Excel and Google Sheets
Cloud AI Development with Amazon Web Services
DevOps on AWS
Continuous Delivery
Creating a Software Development Environment for AWS
Integrating Jupyter Notebook
Integrating Command-Line Tools
Integrating AWS CodePipeline
Basic Docker Setup for Data Science
Other Build Servers: Jenkins, CircleCI, and Travis
Summary
3 Spartan AI Lifecycle
Pragmatic Production Feedback Loop
AWS SageMaker
AWS Glue Feedback Loop
AWS Batch
Docker-based Feedback Loops
Summary
II: AI in the Cloud
4 Cloud AI Development with Google Cloud Platform