Free ebook: Azure Machine Learning


4477.9780735698178_2D00_FB_5F00_732F5A13[1]You’re into Machine Learning, got into Azure ML, looked at my couple of blogs about it and want to take it to the next level?

Microsoft released an eBook for that exact purpose:

Free ebook: Azure Machine Learning (Microsoft Azure Essentials)

That book is targeted at people who want to get better with Azure ML tool:  developer, data scientist, data analyst, etc.  .  It goes into a bit of conceptual (Machine Learning in general) and quickly dive into practical examples with step by step and screen shots.

The book is available in ePub (ideal for commuting!), PDF & Mobi.

Here are the chapters:

  • Chapter 1, “Introduction to the science of data,” shows how Azure Machine Learning represents a critical step forward in democratizing data science by making available a fully-managed cloud service for building predictive analytics solutions.
  • Chapter 2, “Getting started with Azure Machine Learning,” covers the basic concepts behind the science and methodology of predictive analytics.
  • Chapter 3, “Using Azure ML Studio,” explores the basic fundamentals of Azure Machine Learning Studio and helps you get started on your path towards data science greatness.
  • Chapter 4, “Creating Azure ML client and server applications.” expands on a working Azure Machine Learning predictive model and explores the types of client and server applications that you can create to consume Azure Machine Learning web services.
  • Chapter 5, “Regression analytics,” takes a deeper look at some of the more advanced machine learning algorithms that are exposed in Azure ML Studio.
  • Chapter 6, “Cluster analytics,” explores scenarios where the machine conducts its own analysis on the dataset, determines relationships, infers logical groupings, and generally attempts to make sense of chaos by literally determining the forests from the trees.
  • Chapter 7, “The Azure ML Matchbox recommender,” explains one of the most powerful and pervasive implementations of predictive analytics in use today on the web today and how it is crucial to success in many consumer industries.
  • Chapter 8, “Retraining Azure ML models,” explores the mechanisms for incorporating “continuous learning” into the workflow for our predictive models.

Enjoy!

 

Advertisements

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s