Data Science Process

Over the past decade, organizations have seen a rapid growth in data. Harnessing insight from that data is crucial to the growth and sustenance of these organizations. Yet, groups chartered with extracting value from data fail for various reasons. In this chapter, we will cover how organizations can avoid the potential pitfalls of data science.

There is a larger discussion about the quality and governance of data, which we will not be covering here. Experienced data scientists recognize the challenges with data and account for them in their processes. In general, some of these challenges include the following:

Poor data quality and consistency
Silos of data driven by individual business teams
Technologies that are hard to integrate with other data sources
The inability to deal with the Vs of big data: volume, velocity, variety, and veracity

In some cases...

Michael L. Friscia May 25, 2019

I attended Live AI in Orlando in December 2018, shortly after this book came out, and the book was a great refresher on doing many things I had forgotten how to do. The only trouble is that Azure has changed their interface a little and added many new features. So some of the screen shots in this book are outdated but the information is accurate. They also make references to tutorials, they still exist in the Azure GitHub but not in the same way in Azure portal as the book references.The problem with Machine Learning is that there are too many different aspects to cover. I think this book does a great job at touching on most of them. But for me, I wanted something to help navigate the Azure tools to give me a kick in the right direction. I know Python, I've worked with R and I've done a handful of tensorflow stuff on Linux docker images. But my work is entirely in Azure.If you are new to Azure and Machine Learning, I think this book is good. It summarizes a lot of what you can find in the Microsoft tutorials online for getting started with Azure ML studio and puts it into easy to follow steps. But be forewarned that Azure changes often, the concepts in this book remain solid but in another year, most of the steps will likely be much different. The change between December and now is pretty big in that Azure has added numerous new features to their AI/ML offerings. Having worked in Azure for a couple of years, I know in 6 months it will be even more different which will probably make this book obsolete by the summer of 2020 except for advanced Azure users that can translate this book to the newer Azure interface.I do recommend this book but keep i mind, it is exactly what the title says it is. It is not a book to teach how to do machine learning, it is a hands on book using microsoft experiments published in GitHub for use on the Azure platform that will help you understand how to use Azure tools for machine learning.

Amazon Verified review

Colin Dec 12, 2018

For the price I was expecting something far more in-depth. It's a big book but most of it is just screenshots, and much of the rest is just blurb/ML hype. Terminology isn't explained and the authors skim over most detail - eg we are informed that R code can be embedded into ML studio to enable you to create bespoke ML algorithms, but there is no detail on how to actually go about doing this. Similarly there is a lack of detail on the other available functions in ML studio. Also, whilst there is a whole chapter on the data science lifecycle process, there is little detail on the application of this - ie what I, as a data scientist who is new to Azure, need to do to get from raw data in a lake to a fully deployed embedded ML solution.

Md Abu S. Chowdhury Apr 26, 2019

Very poor Graphics Contents.. Unable to read many image contents

Hands-On Machine Learning with Azure: Build powerful models with cognitive machine learning and artificial intelligence

What do you get with Print?

Hands-On Machine Learning with Azure

Data Science Process

TDSP stages

Tools for TDSP

IDEAR tool for R

Summary

Page 1 of 4

Key benefits

Description

Who is this book for?

What you will learn

Product Details

What do you get with Print?

Product Details

Frequently bought together

Table of Contents

Recommendations for you

Customer reviews

People who bought this also bought

About the 6 authors

FAQs

Hands-On Machine Learning with Azure: Build powerful models with cognitive machine learning and artificial intelligence

What do you get with Print?

Contact Details

Shipping Address

Billing Address

Key benefits

Description

Who is this book for?

What you will learn

Product Details

What do you get with Print?

Contact Details

Shipping Address

Billing Address

Product Details

Packt Subscriptions

Frequently bought together

Table of Contents

Recommendations for you

Customer reviews

People who bought this also bought

About the 6 authors

FAQs