How to Use Machine Learning in Microsoft Sentinel to Enhance Your Cybersecurity

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Welcome to this tutorial on how to leverage machine learning (ML) within Microsoft Sentinel to detect cybersecurity incidents. In this video, I will show you how you can use ML to analyze data and detect incidents and anomalies that would be difficult to spot using traditional security methods.

Microsoft Sentinel provides a powerful security information and event management (SIEM) platform that aggregates data from multiple sources. By integrating ML, you can take your cybersecurity capabilities to the next level and get ahead of potential threats.

Follow along with me in this tutorial to learn how to build Microsoft Sentinel use cases using ML, playbooks, and KQL. You will discover how to detect and respond to cyber threats more efficiently and effectively, reducing the risk of data breaches and other security incidents.

By the end of this tutorial, you will have the knowledge and skills you need to start leveraging machine learning within Microsoft Sentinel to enhance your cybersecurity.

Don't forget to like and subscribe to our channel for more tutorials on cybersecurity and data science.

Hashtags: #MicrosoftSentinel #MachineLearning #cybersecurity #SIEM #playbooks #KQL #dataanalysis #data science.

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Just brilliant - exactly what I have been looking for. Dank je wel.

snoopdoggywuf
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Nice... Any Vid on Linux Servers? Most people focus on windows servers

wearewhoweare
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Hi, do u want to say that sentinal anomalies detection is not powerful? Can we use high level machine learning model and integrate into it

traveloguer