Predictive Analytics with Microsoft Azure Machine Learning

by Fontama, Valentine
5 out of 5 Customer Rating
ISBN: 9781484212011
Availability:
$29.99

Available Offers

20% Off In Cart
See Details
Offer Details
Get 20% off on pre-owned items, available in store and online. Offer valid May 23-26, 2025. This offer cannot be combined with other discounts or coupons and does not apply to previous purchases. Offer cannot be used to buy gift cards or items labeled as 'New' on HPB.com. Sale prices will be reflected in your cart.

Pickup at HPB West Lane Avenue Out of stock at HPB West Lane Avenue Check other stores
FREE -
Ship to Me
$3.99 - Get it May 30 - Jun 2
Only 1 left

Overview

Predictive Analytics with Microsoft Azure Machine Learning, Second Edition is a practical tutorial introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book provides a thorough overview of the Microsoft Azure Machine Learning service released for general availability on February 18th, 2015 with practical guidance for building recommenders, propensity models, and churn and predictive maintenance models.

The authors use task oriented descriptions and concrete end-to-end examples to ensure that the reader can immediately begin using this new service. The book describes all aspects of the service from data ingress to applying machine learning, evaluating the models, and deploying them as web services.

Learn how you can quickly build and deploy sophisticated predictive models with the new Azure Machine Learning from Microsoft.

What's New in the Second Edition?

Five new chapters have been added with practical detailed coverage of:

  • Python Integration - a new feature announced February 2015
  • Data preparation and feature selection
  • Data visualization with Power BI
  • Recommendation engines
  • Selling your models on Azure Marketplace

  • Format: Trade Paperback
  • Author: Fontama, Valentine
  • ISBN: 9781484212011
  • Condition: Used
  • Dimensions: 9.21 x 0.67
  • Number Of Pages: 291
  • Publication Year: 2015

Customer Reviews