Adenman Posted April 9, 2021 Share Posted April 9, 2021 With this book, you'll learn how to use Python libraries such as TensorFlow and scikit-learn to implement the latest artificial intelligence (AI) techniques and handle challenges faced by cybersecurity researchers. You'll begin by exploring various machine learning (ML) techniques and tips for setting up a secure lab environment. Next, you'll implement key ML algorithms such as clustering, gradient boosting, random forest, and XGBoost. The book will guide you through constructing classifiers and features for malware, which you'll train and test on real samples. As you progress, you'll build self-learning, reliant systems to handle cybersecurity tasks such as identifying malicious URLs, spam email detection, intrusion detection, network protection, and tracking user and process behavior. Later, you'll apply generative adversarial networks (GANs) and autoencoders to advanced security tasks. Finally, you'll delve into secure and private AI to protect the privacy rights of consumers using your ML models. By the end of this book, you'll have the skills you need to tackle real-world problems faced in the cybersecurity domain using a recipe-based approach. Mac & PC Screenshots Website Virus Scan https://www.bitsdujour.com/software/machine-learning-for-cybersecurity-cookbook-3199-value-free-for-a-limited-time/in=today-100-percent https://bitsdujour.tradepub.com/free/w_pacb136/prgm.cgi Link to comment Share on other sites More sharing options...
Adenman Posted April 27, 2021 Author Share Posted April 27, 2021 The giveaway has expired and no longer available to participate. Link to comment Share on other sites More sharing options...
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