Predictive Analytics with Microsoft Azure Machine Learning: Build and Deploy Actionable Solutions in Minutes
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Data Science and Machine Learning are in high demand, as customers are increasingly looking for ways to glean insights from all their data. More customers now realize that Business Intelligence is not enough as the volume, speed and complexity of data now defy traditional analytics tools. While Business Intelligence addresses descriptive and diagnostic analysis, Data Science unlocks new opportunities through predictive and prescriptive analysis.
The purpose of this book is to provide a gentle and instructionally organized introduction to the field of data science and machine learning, with a focus on building and deploying predictive models.
The book also provides a thorough overview of the Microsoft Azure Machine Learning service using task oriented descriptions and concrete end-to-end examples, sufficient to ensure the reader can immediately begin using this important new service. It describes all aspects of the service from data ingress to applying machine learning and evaluating the resulting model, to deploying the resulting model as a machine learning web service. Finally, this book attempts to have minimal dependencies, so that you can fairly easily pick and choose chapters to read. When dependencies do exist, they are listed at the start and end of the chapter.
The simplicity of this new service from Microsoft will help to take Data Science and Machine Learning to a much broader audience than existing products in this space. Learn how you can quickly build and deploy sophisticated predictive models as machine learning web services with the new Azure Machine Learning service from Microsoft.
ASIN : B01JCTWOX0
Publisher : Apress; 1st edition (November 25, 2014)
Publication date : November 25, 2014
Language : English
File size : 3961 KB
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Print length : 272 pages
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12 reviews for Predictive Analytics with Microsoft Azure Machine Learning: Build and Deploy Actionable Solutions in Minutes
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Sofia –
Great Book and … great packaging!
Very well packaged and delivered. A good book
koppinjo –
The book holds your hand through creating some ML workflows but lacks a good description of WHY you are being instructed to put
Lots of repeated sentences throughout the book, information/sources are outdated which means if you are trying to code along with it, it will not always work. The book holds your hand through creating some ML workflows but lacks a good description of WHY you are being instructed to put things together in a certain way, and potential pitfalls or improvements.
hxy0135 NJ –
Good book
The book gets you a quick start with Microsoft Azure Machine Learning technology. I believe a reader needs to know some basic concepts of data mining to effectively follow through the book.The book does have some good examples and detail descriptions for the cases of common use scenarios of industries. That is the most attractive part of the book for me. According to the review of the book, the book would contain a practical example of Recommendation system. That is one of reason I bought the book. But It only mentioned the principles to build a Recommendation system, I did not see a concrete sophisticated example for Recommendation system. I am little disappointed at that.The book also missed some information on where a user can find downloads of the workspaces and data used by the examples. I wrote to the authors, they quickly replied my inquiry and actively working on it.
Binh N. Cao –
must buy
this book is a must buy. I know all the authors who wrote this book and what they teach here is fundamental to machine learning and Azure ML in general.
Andrew –
… you rent this book before buying it so you better understand if it is for you
I suggest you rent this book before buying it so you better understand if it is for you. The book is very short and generic explaining more the mechanics rather than interpreting results and helping you to make a decision.
Leandro –
Don’t buy the paper book – Print’s quality is very poor.
Print’s quality is very poor. It’s impossible to see and understand the pictures that work as example in this book. For this reason, some times you don’t know what to do. I’d like to have my money back!But the content works well!
Margaret Rolph –
Five Stars
Excellent tutorial for using Microsoft Azure machine learning. Highly recommended.
Donald L. Mitchell –
Five Stars
Well written introduction to Machine Learning with ML Studio.
Thierry Vallaud –
Un livre qui permet d’apprendre par étape et faire des modèles de data mining sur un des meilleurs soft en mode full SAAS du moment[…]Et cela marche par rapport à d’autres outils SAASCe n’est pas qu’un ETLLes aglos sont conviviaux…..
El Monono –
The book’s authors have a deep understanding of data science and Azure Machine Learning (AML). This is evinced by the practical easy-to-follow models on business critical problems like propensity to buy, segmentation and churn amongst others discussed in the book.This hands-on guide to AML would be useful to those requiring a basic grounding in data science as well as act as an AML reference for the more experienced data scientists.I found this book resourceful because I am currently doing churn analysis. Thus, I can state with a fair degree of certainty that if you’re thinking about frameworks for tackling practical business problems with machine learning, this book, which clearly demonstrates how it can be achieved via AML, is the book you need.
Charles –
Très bon livre qui permet de comprendre le fonctionnement de azure ml.Il y quelques erreurs mais au finale c est un très bon book
Duncan –
The examples were good and well explained but I really need far more detail on what each module does, what it’s settings do and when it should be used – like a Petzold book.