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Introduction to machine learning for security analysts
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README.md

Machine-Learning-for-Security-Analysts

Introduction to machine learning for security analysts

Slides: https://www.slideshare.net/GTKlondike/machine-learning-for-security-analysts

This workshop is intented to be interactive. Checkout the Google Colab links below to work with the code for this workshop:

  1. Spam filter from scratch - https://colab.research.google.com/drive/1M7xmKHzZrcTXI5c83XIXvey2_OJSZHnb

  2. Spam filter using Scikit-Learn - https://colab.research.google.com/drive/1AmswB68K61yGN4FQdiejcYMap3T8L4Hq

  3. Malicious URL predictor - https://colab.research.google.com/drive/1vkTapu6gNVKKebKJH7oTOdyaTYTmKgHi

The narrative across all three demos is to first build a spam filter from scratch using the techniques described in the presentation.

Then, we'll demonstrate how abstraction libraries like Scikit-Learn makes building and training models even easier by showing the plug-and-play of nature of the library.

Finally, we will use the exact same technique to build a malicious URL predictor.

The added benefit of having these demos on Google Colab is that it allows people to take the code home and look at what it's doing, in an interactive browser session.

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