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Machine Learning in the Cloud - Is it Right for You? 

Due to new technology stacks and workloads, I&O leaders face many challenges and trade-offs when determining the optimal AI environment. Gain an understanding of how you can make the best decision on Machine Learning in the Cloud by downloading the Gartner Analyst Report.


Read about Key Challenges & Recommendations:


  • Reduce Operational Complexity and Minimize Training Times
  • Determine Your Optimal AI Environment and Best Data Management Tools
  • Increase Efficiency of Machine Learning Workloads
  • Select a Deployment Platform for Optimal TCO
  • Deliver Faster Time to Product by Aligning Infrastructure to Existing Investments and In-House Skill Sets


Learn How to Evaluate ML/DL Development Models Across 6 Key Parameters:

  1. Infrastructure choice
  2. TCO
  3. Data Gravity and Integration
  4. Performance
  5. Flexibility
  6. Skills & Operational Simplicity


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Use This Decision Framework to Determine If Machine Learning Should Run In The Cloud, October 2017

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All statements in this report attributable to Gartner represent Joyent's interpretation of data, research opinion or viewpoints published as part of a syndicated subscription service by Gartner, Inc., and have not been reviewed by Gartner. Each Gartner publication speaks as of its original publication date (and not as of the date of this [presentation/report]). The opinions expressed in Gartner publications are not representations of fact, and are subject to change without notice.