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5 Hardware Accelerators Every Data Scientist Should Leverage

Smart Data Collective

Among other benefits, this helps make sure global computing resources are used as efficiently as possible and allows data science companies to take advantage of these resources at a reduced cost. IBM Watson Studio. IBM Watson Studio is a very popular solution for handling machine learning and data science tasks. Neptune.ai.

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Replacing Legacy. Part 5: Cloud, SaaS Legacy, and AI

Analysts Corner

Here, we reflect on the reasoning behind the past, current, and future trends: Cloud deployments, SaaS (Software-as-a-Service), and AI (Artificial Intelligence). There might be various reasons behind such a move, such as increased costs, imposed new regulations, not following SLA (Service Level Agreement), or a failed reputation.

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Testing New AI Applications is Crucial Before Bringing them to Market

Smart Data Collective

Mistakes can be minor, and they can be dangerous or lead to significant financial losses for any company that relies on your artificial intelligence algorithms. Modern methods of software development take a more systematic approach to testing, in accordance with the IBM Rational Unified Process (RUP).

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7 Ways To Prevent Data Breaches With Technology And Training

Smart Data Collective

According to IBM’s cost of data breach report 2020, the average cost of data breach in the United States alone is $8 million. As a result, most employees can easily get away even after committing security blunders that can cost your business millions of dollars. Give More Control to Employees.

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How The Cloud Made ‘Data-Driven Culture’ Possible | Part 2: Cloud Adoption

BizAcuity

Quick recap from the previous blog- The cloud is better than on-premises solutions for the following reasons: Cost cutting: Renting and sharing resources instead of building on your own. IaaS is delivered by all the major players including AWS, Azure, Cisco, IBM, Oracle and Google. Starting with cloud adoption.

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Data Quality Best Practices to Discover the Hidden Potential of Dirty Data in Health Care

Dataversity

Dirty data – data that is inaccurate, incomplete, or inconsistent – costs the U.S. trillion per year, according to IBM.

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Big Data Is Already A Thing Of The Past: Welcome To Big Data AI

Smart Data Collective

Not long ago, big data was one of the most talked about tech trends , as was artificial intelligence (AI). Then, it intelligently assigns a risk grade from A to F, with an F-graded business most likely to have the highest claims costs. IBM is the official technology partner of Wimbledon, and it has collected 62.8

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