Watch full webinar here: https://bit.ly/3hpTRep
AI and ML help automate many of the enterprise tasks. What role do they play in cloud technologies? And, different cloud service providers (CSP) claim AI and ML capabilities within their technologies. But which one has better support for data science? Does any one CSP provide better tools and automation for data scientists to perform their analysis with ease and speed? The Chief AI Architect from UST will elaborate on the differences between cloud technologies for supporting AI, ML, and data science. Do you have additional questions that you want answered on this subject? Then bring them on.
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Role of Unified AI and ML in Cloud Technologies. Which Cloud Service Provider Better Supports Data Science?
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2. Role of Unified AI and ML in Cloud
Technologies. Which Cloud Service
Provider Better Supports Data Science?
Adnan Masood, PhD.
Chief AI Architect, UST
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And the Oscar goes to ..
• If your data and compute resides in the cloud, it would make way more
sense to use the automated machine learning offered by that specific
cloud provider for all practical purposes. If you have a hybrid model, try to
keep your automated machine learning compute close to data you plan to
use, wherever it reside
• Generally speaking, cloud compute and storage resources for automated
machine learning can get expensive quickly , providing you are working
with large models and doing multiple simultaneous experiments. If you
have compute resources and data available in an on-prem scenario, that
could be an ideal playground without increasing your hyperscaler’s bill.
• This however comes with the responsibility of setting up the
infrastructure and do the setup for an on-prem toolkit. So if cost is not a
major concern and you want to quickly explore what automated machine
learning can do for you, cloud based toolkits would make an ideal
companion
• Your relationship with your cloud provider is important, you might be also
be able multi-service discounts.