Cybercriminals are always on the lookout for opportunities to profit from security weaknesses. Meanwhile, the COVID pandemic lead accelerated cloud transformation has rendered many of the assumptions of legacy security approaches obsolete. Enterprises are realizing that modern cyber-attacks won’t be stopped by a purely preventive strategy. In fact, it’s almost a given that with sufficient time, motivation, and resources an attacker will always find a point of entry.
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One of the biggest challenges security teams are faced with is doing more with less in conjunction with protecting the growing list of attack surfaces from being breached.
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Security organizations are overworked and constrained. As more systems and users come online, it becomes more difficult to manage alerts and administer access to sometimes hundreds of applications for thousands of employees.
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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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