Charles Givre – Preparing and Exploring Security Data for Machine Learning

Salepage : Charles Givre – Preparing and Exploring Security Data for Machine Learning
Archive : Charles Givre – Preparing and Exploring Security Data for Machine Learning Digital Download
Delivery : Digital Download Immediately

What is the purpose of this video course, and why is it important?

Security is undoubtedly the most significant field in the IT business today. With more trade and business being performed online every day, keeping data secure and identifying and repelling assaults is critical for any enterprise. Machine learning is one field that has enormous potential in the fight against hackers and their attacks. It is no longer a theoretical goal to use these systems’ rising strength and finesse to combat invasions and data theft. Indeed, machine learning is being utilized to defend systems and networks in a growing number of sectors and companies, so it’s no surprise that there’s a growing demand for professional and trained security specialists who can apply data science approaches to the task of data security.

This video will show you how to quickly and efficiently ingest a variety of data types commonly used in security settings and prepare them for analysis in the Python data science ecosystem if you’re a security engineer, network analyst, or anyone else charged with protecting your organization’s valuable IT system and data. Charles Givre, a cyber security professional and data scientist, introduces the fundamentals of vectorized computing as they apply to security. One of the most difficult problems for anybody interested in advanced analysis and machine learning is gathering and preparing data. This video will teach you how to leverage the Pandas ecosystem to acquire, process, and examine security data fast and effectively for advanced analysis and machine learning.

This video is one of three in a series aimed for security professionals who want to understand how to utilize and apply data science to their most difficult security challenges. It focuses on tools and techniques that are directly applicable to the business, and it use security challenges and datasets to guide you through the complete data science process from start to finish.

What you’ll learn—and how you might put it to use

How to Prepare Security Data using Pandas

How to Import, Process, and Summarize Multidimensional Data

How to rapidly extract, convert, and load (ETL) security data from several sources into the Pandas environment, extract features, and prepare the data for machine learning.

This video course is designed for you because…

You’re a security professional with some scripting experience who wants to use data science approaches to examine data more effectively.

You’re a network analyst with some scripting experience who wants to employ machine learning approaches to improve network security.

Prerequisites:

Python programming skills ranging from beginning to intermediate is required.

You should be conversant with the principles of security and networking.

You should have a general understanding of basic statistical principles.

Materials or downloads required ahead of time:

It is recommended that you utilize the Griffon Virtual Machine for Data Science, which may be found at https://github.com/gtkcyber/griffon-vm. (Griffon is a virtual computer that comes preconfigured with all data sources and tools.)

You should have access to a computer with at least 8 GB of RAM and 20 to 30 GB of hard drive space available.

More from Categories : SEO Website & Design