The document highlights the significance of machine learning in improving data-driven decision-making across industries, illustrating its impact on companies with notable revenue growth. It emphasizes IBM's machine learning solutions, which facilitate real-time responses and personalized healthcare plans. Additionally, it provides legal disclaimers about the information presented, indicating variability in product availability and performance outcomes.

1. IBM Machine
Learning
Rob Thomas
General Manager,
IBM Analytics
@robdthomas

2. SOURCE: http://www.tennessean.com/story/money/tech/2014/05/02/jj-rosen-popular-search-engines-skim-surface/8636081/
Over
of the world’s data
cannot be googled

3. Facebook 56%
Welltower 50%
Alexion Pharmaceuticals 37%
Salesforce.com 32%
Under Armour 30%
TripAdvisor 25%
Priceline 25%
Cognizant 22%
Alphabet 21%
What fuels the growth
of outperformers?
A sampling of
the top 10 have
one thing in
common….
AVERAGE REVENUE GROWTH OVER 5 YEARS Machine
Learning
SOURCE: Scott Galloway, NYU Stern

4. PHOTO CREDIT: Kyle Harris

5. Productivity: Make both
experienced and novice
data scientists more
productive.
Trust: Confidently deploy
insights knowing they are
generated from the most
current data and trends.
Freedom: Choose the
right language and ML
framework and platform
for your business.
Infuse continuous intelligence throughout the enterprise
Continuous Intelligence:
Machine Learning made simple

6. IBM Machine Learning: Extracted from Watson,
delivered to your private cloud
IBM PRIVATE CLOUD
Cognitive computing
Augmented intelligence
Machine learning IBM Machine Learning

7. Unleash Machine Learning
on the World’s
Most Valuable Data

8. Data and machine learning at work
Real-time response at
point of sale
Ongoing tracking of
risk profile changes
Co-pay based on
risk profile
Using machine learning to personalize prescription plans & lower payments
Argus Healthcare –
Continuous Intelligence in healthcare
THE PROBLEM
Develop personalized prescription
plan for diabetes patients based
on their individual risk profile.
SOLUTION
Classify patients as low, moderate,
high risk of developing diabetes
based on blood sugar, blood
pressure and cholesterol.

9. Share and learn from
the best in machine learning
IBM Machine
Learning Hub
MLHub@us.ibm.com

11. © IBM Corporation 2017. All Rights Reserved.
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LEGAL DISCLAIMER