Every company is concerned about data breaches, and for good reason—according to industry estimates, approximately half of the companies in the U.S. have suffered a data breach. As organizations seek to better secure their environments, they are facing a number of challenges including growing data volumes and expanded attack surfaces, as well as data silos and the inability to enable data-driven decisions about security issues in real time. It is not surprising that security and privacy rank in the top three data-related priorities in TDWI surveys.
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Last year saw a historic number of data breaches that exposed the personal information of millions of individuals to possible risk. In our new 15-minute webinar, we’ll be joined by the Identity Theft Resource Center (ITRC) to review 2022’s threat trends, the risks to businesses, and how employees and consumers can help protect their identity, credit and other personal data.
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Python is the second most popular language and is very easy to start using. It is almost a de-facto standard in machine learning. Here be dragons!
Many machine learning (ML) models are Python pickle files under the hood. The use of pickling conserves memory, enables start-and-stop model training, and makes trained models portable (and, thereby, shareable).
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The only thing constant is change, and change requires oversight and very possibly an overhaul of your processes to support any shifts. The open source world is not exempt. Net, your code isn't static so your processes shouldn't be either. What open source management processes should be in your team's eyeline? How does change im
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