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Hands-On Machine Learning for Cybersecurity

Hands-On Machine Learning for Cybersecurity

By : Halder, Sinan Ozdemir
2.7 (6)
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Hands-On Machine Learning for Cybersecurity

Hands-On Machine Learning for Cybersecurity

2.7 (6)
By: Halder, Sinan Ozdemir

Overview of this book

Cyber threats today are one of the costliest losses that an organization can face. In this book, we use the most efficient tool to solve the big problems that exist in the cybersecurity domain. The book begins by giving you the basics of ML in cybersecurity using Python and its libraries. You will explore various ML domains (such as time series analysis and ensemble modeling) to get your foundations right. You will implement various examples such as building system to identify malicious URLs, and building a program to detect fraudulent emails and spam. Later, you will learn how to make effective use of K-means algorithm to develop a solution to detect and alert you to any malicious activity in the network. Also learn how to implement biometrics and fingerprint to validate whether the user is a legitimate user or not. Finally, you will see how we change the game with TensorFlow and learn how deep learning is effective for creating models and training systems
Table of Contents (13 chapters)
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1
Basics of Machine Learning in Cybersecurity
5
Using Data Science to Catch Email Fraud and Spam

Introduction to TensorFlow

TensorFlow is written in C++ and comprises two languages in the frontend. They are C++ and Python. Since most developers code in Python, the Python frontend is more developed than the C++ one. However, the C++ frontend's low-level API is good for running embedded systems.

TensorFlow was designed for probabilistic systems and gives flexibility to users to run models with ease, and across a variety of platforms. With TensorFlow, it is extremely easy to optimize various machine learning algorithms without having to set gradients at the beginning of the code, which is quite difficult. TensorFlow comes packed with TensorBoard, which helps visualize the flow with graphs and loss functions. The following screenshot shows the TensorFlow website:

TensorFlow, with all these capabilities, makes it super easy to deploy and build for industry use cases that...

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