CTO Straight Talk - Issue 2 - 38

provides a global platform and social

creators reach consumers directly.

would improve their work or lives.

network to foster discovery and

There is no middle man that tells

Examples of APIs offered in the

community collaboration. To improve

app developers what to build. They

marketplace today include those

the user experience, Mendeley was

publish to an online marketplace and

offering recommendations for similar

looking to anticipate the behavior of

consumers select what's best or most

products purchased, detecting

new users in their initial adoption

relevant for their needs.

anomalies in data, and performing

and engagement phase. Within
two weeks of implementing Azure
Machine Learning, developers were
able to create a predictive model
that was 30% more accurate than an
earlier model that had taken them
months to develop on their own. Not
only is Mendeley able to iterate and
deploy models three to five times
faster, it can pinpoint users' needs
with much greater confidence.

We are trying to emulate this by
adding machine learning models and
packages to the Azure Marketplace: a
marketplace where data scientists can
show their creativity and monetize it.
By "data scientists" I mean engineers
and physicists and statisticians and
business school graduates who love
data, are passionate about developing
analytical models, but haven't had the
tools to build full solutions.

Building the Data Science
Economy

With a ready-made marketplace to

We're beginning to see what happens

can develop innovative analytical

when we make machine learning

models, package them into APIs

accessible to enterprises. But what

(application program interfaces)

about making machine learning in

that others can consume, and

the cloud available to individuals?

publish these APIs. Developers and

I'm thinking here mostly about

consumers can then access the same

the supply side of the market for

marketplace, search or browse for

advanced analytics.

APIs, and pay for a specific API they

The cloud as a platform has already
given us the app economy, where app

showcase their skills, data scientists

wish to consume - something that
they would, in turn, use to deliver

sentiment analysis on textual data
such as social media feeds or web
pages. These marketplace APIs can
be consumed in other applications
or even in Excel spreadsheets.
They support transactions in many
currencies and offer an efficient
platform for building a data science
economy. We expect eventually to
host millions of such analytics APIs
in the cloud.
Machine learning is poised to be
a game changer across industries
and an important technology for
improving our personal lives. We
are rapidly realizing the vision of
democratizing the use of machine
learning by both enterprises and
individuals. Businesses should take
the time now to understand the true
potential of machine learning and
advanced analytics within their
own organizations.

a predictive analytics solution that

The Takeaways
* Machine learning - a branch of artificial intelligence that involves advanced statistics - is a tool for
training computers to make data-based predictions. When you can make accurate predictions, you have
the power to optimize business systems and processes.
* Thanks to the explosion of big data and the advent of cloud computing, machine learning is now
accessible to a wide array of organizations and may soon touch many aspects of our lives, as Microsoft is
exploring in its Intelligent Cloud project.
* Machine learning may be a game changer for businesses and individuals. Now is the time to learn about its potential.

CTO Straight Talk | 38

CTO Straight Talk - Issue 2

Table of Contents for the Digital Edition of CTO Straight Talk - Issue 2