⇲ Plan & Architect
⇲ Design & Build
⇲ Implement & Scale
DATA STRATEGY
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A startup in digital health trained a risk model to open up a robust, precise, and scalable processing pipeline so providers could move faster, and patients could move with confidence after spinal surgery. 
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    ⇲ Dive Into
    PREDICTIVE ANALYTICS
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    Thwart errors, relieve in-take form exhaustion, and build a more accurate data picture for patients in chronic pain? Those who prefer the natural albeit comprehensive path to health and wellness said: sign me up. 
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      MACHINE VISION
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      Using a dynamic machine vision solution for detecting plaques in the carotid artery and providing care teams with rapid answers, saves lives with early disease detection and monitoring. 
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        INTELLIGENT AUTOMATION
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        This global law firm needed to be fast, adaptive, and provide unrivaled client service under pressure, intelligent automation did just that plus it made time for what matters most: meaningful human interactions. 
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          ⇲ Learn
          ⇲ Explore AI Impact
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          Mushrooms, Goats, and Machine Learning: What do they all have in common? You may never know unless you get started exploring the fundamentals of Machine Learning with Dr. Tim Oates, Synaptiq's Chief Data Scientist. You can read and visualize his new book in Python, tinker with inputs, and practice machine learning techniques for free. 
          Start Chapter 1 Now ⇢ 

           
            ⇲ Artificial Intelligence Quotient

            How Should My Company Prioritize AIQ™ Capabilities?

             

               

               

               

              Start With Your AIQ Score

                Lisa Peacock

                Lisa writes about the intersection of human-centered design on AI and Machine Learning, the power of using your real brand voice, and creativity in business. She likes golden retrievers, singing in the shower, and throws a mean soiree´.

                For the love of a data scientist! It’s time. (To start deploying your AI solutions).

                Are we comparing our data scientists to God with that title? Not quite. Disrupting an old, informal idiom your exasperated mom might have once used to get your attention? Perhaps. Filling in the blank on our favorite MadLib? Maybe. Being provocative to get you to ask us more AI questions? Definitely. But what is without question, is the ethical responsibility that the data science field will need to demonstrate over the next decade. Our global problems are big. They are on the rise. And everyone needs to be paying attention and saying yes to AI to solve them. It's time.