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1
Introduction
2
Important Warning
3
Agenda
4
Big Data
5
Big Data Challenges
6
Learning
7
Applications
8
Fraud Detection
9
Machine Learning
10
Spam Filtering
11
Regression
12
Support Vector Machines
13
Why Should We Care
14
What a Data Scientist Should Be
15
Statistical Relevance
16
Angels Evolved
17
The Bad Guys
18
How to Get Started
19
Big Differences
20
Takeaway
21
Improving Data Quality
Description:
Explore the intersection of machine learning and information security in this BSidesLV conference talk by Alex Pinto. Delve into the challenges of big data, learn about various machine learning applications in security, including fraud detection and spam filtering, and understand the importance of statistical relevance. Discover what makes a good data scientist, examine the evolving landscape of cyber threats, and gain insights on improving data quality. Get practical advice on how to start implementing machine learning in information security and understand the key differences between traditional and data-driven approaches.

Using Machine Learning to Support Information Security

BSidesLV
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