Mehdi Roopaei - Monetizing Machine Learning: quickly turn python ml ideas into web applications on the ... serverless cloud

Manuel Amunategui and Mehdi Roopaei

Monetizing Machine Learning Quickly Turn Python ML Ideas into Web Applications on the Serverless Cloud

ISBN 978-1-4842-3872-1 e-ISBN 978-1-4842-3873-8

https://doi.org/10.1007/978-1-4842-3873-8

Library of Congress Control Number: 2018956745

Manuel Amunategui, Mehdi Roopaei 2018

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Introduction

We wont focus on becoming a data scientist as an end goal; there are plenty of books on that topic already. Instead, well focus on getting machine learning products to market quickly, simply, and with the user/customer in mind at all times! Thats what is missing in this professions educational syllabus. If you build first and then talk to your customer, your pipelines will be flawed and your solutions will miss their target. I have redrawn Drew Conways Data Science Venn Diagram with the customer as top priority (Figure ).

Mehdi and I worked hard on the content of this book. We took our time to develop the concepts, making sure they were of practical use to our reader (i.e., our customer always keep the customer in mind at all times). I built the material and Mehdi edited it. This is an ambitious book in terms of scope and technologies covered. Choices and compromises had to be made to focus on the quickest ways of getting practical use out of the material. The tools are constantly changing. Some things in this book are going to be stale by the time you read them, and that is OK (you can go to the GitHub repo for updates). Here, everything changes all the time, but things tend to change for the better! So, learning new tricks often means learning better, faster, and more powerful ways to do things. This book will not only show you how to build web applications but also point you in the right direction to deepen your knowledge in those areas of particular interest.

If this was a class, Id have you sign a compete agreement : yes, the opposite of a non-compete. I would have you go through this book, understand the tools, and then copy them and make them your own. These are meant to be templates to quickly get your platforms up and running to focus on the bigger things, to build impactful tools for your customers and friends. When you understand this, thats the day you graduate with all the entitlements and privileges of being called a data science professional.

Cloud providers have gone to great efforts to improve web hosting solutions and bring costs down. The recent advent of the serverless option, which abstracts a large swath of the configuring process, is available on three of the four cloud providers covered in this book. This means you can get your projects up and running on fully managed platforms, with automatic load-balancing, throughput scaling, fast deployments, etc., without having to select, configure, or worry about any of it. The level of disengagement with these architectural and monitoring options is up to you. You can choose what you want to control and what you want to delegate to the provider. One thing is guaranteed: the site will automatically adjust with traffic and offer unparalleled uptime.