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Preface
Chapter 1. Basics of Machine Learning in Cybersecurity
Chapter 2. Time Series Analysis and Ensemble Modeling
Chapter 3. Segregating Legitimate and Lousy URLs
Chapter 4. Knocking Down CAPTCHAs
Chapter 5. Using Data Science to Catch Email Fraud and Spam
Chapter 6. Efficient Network Anomaly Detection Using k-means
Chapter 7. Decision Tree and Context-Based Malicious Event Detection
Chapter 8. Catching Impersonators and Hackers Red Handed
Chapter 9. Changing the Game with TensorFlow
Chapter 10. Financial Fraud and How Deep Learning Can Mitigate It
Chapter 11. Case Studies
Other Books You May Enjoy
Index
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