Description
Machine learning is disrupting cybersecurity to a greater extent than almost any other industry. Many problems in cyber security are well suited to the application of machine learning as they often involve some form of anomaly detection on very large volumes of data. This course deals the most found issues in cybersecurity such as malware, anomalies detection, SQL injection, credit card fraud, bots, spams and phishing. All these problems are covered in case studies. Section 1: Statistics - Machine LearningLecture 1: Central Tendency (Preview)Lecture 2: Measures Dispersion (Preview)Lecture 3: Data Visualization (Preview)Lecture 4: Confusion Matrix, Accuracy and KappaSection 2: Case StudiesLecture 5: Introduction to Payment Fraud (Preview)Lecture 6: Machine Learning in Payment FraudLecture 7: NO CODING Machine Learning in Payment FraudLecture 8: Introduction to MalwareLecture 9: Machine Learning in MalwareLecture 10: Introduction to PhishingLecture 11: Machine Learning in PhishingLecture 12: Introduction to IDSLecture 13: Machine Learning in IDSLecture 14: Introduction to SpamLecture 15: Machine Learning in SpamLecture 16: Introduction to Twitter Bot DetectorLecture 17: Machine Learning in Twitter Bot DetectorLecture 18: Introduction to Malicious SQL InjectionLecture 19: Machine Learning in SQL InjectionLecture 20: NO CODE Machine Learning in Medical Fraud Detection (Preview)Data. zip
