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Machine learning

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Machine Learning is to the 21st Century, what the Industrial Revolution was to the 18th Century. We are entering the era of Continuous Intelligence. http://www.forbes.com/sites/ibm/2017/02/15/machine-learning-ushers-in-a-world-of-continuous-intelligence/#246de3604c62

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Machine learning

  1. 1. IBM Machine Learning Rob Thomas General Manager, IBM Analytics @robdthomas
  2. 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. 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. 4. PHOTO CREDIT: Kyle Harris
  5. 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. 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. 7. Unleash Machine Learning on the World’s Most Valuable Data
  8. 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. 9. Share and learn from the best in machine learning IBM Machine Learning Hub MLHub@us.ibm.com
  10. 10. © IBM Corporation 2017. All Rights Reserved. • The information contained in this publication is provided for informational purposes only. While efforts were made to verify the completeness and accuracy of the information contained in this publication, it is provided AS IS without warranty of any kind, express or implied. In addition, this information is based on IBM’s current product plans and strategy, which are subject to change by IBM without notice. IBM shall not be responsible for any damages arising out of the use of, or otherwise related to, this publication or any other materials. Nothing contained in this publication is intended to, nor shall have the effect of, creating any warranties or representations from IBM or its suppliers or licensors, or altering the terms and conditions of the applicable license agreement governing the use of IBM software. • References in this presentation to IBM products, programs, or services do not imply that they will be available in all countries in which IBM operates. Product release dates and/or capabilities referenced in this presentation may change at any time at IBM’s sole discretion based on market opportunities or other factors, and are not intended to be a commitment to future product or feature availability in any way. Nothing contained in these materials is intended to, nor shall have the effect of, stating or implying that any activities undertaken by you will result in any specific sales, revenue growth or other results. • All customer examples described are presented as illustrations of how those customers have used IBM products and the results they may have achieved. Actual environmental costs and performance characteristics may vary by customer. • IBM, the IBM logo, and ibm.com are trademarks of International Business Machines Corporation in the United States, other countries, or both. LEGAL DISCLAIMER

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