Production Machine Learning Monitoring- Principles, Patterns and Techniques
Practical deep dive on production monitoring of machine learning models, covering standard techniques and advanced paradigms like concept drift, outlier detection, and explainability, with hands-on examples and architectural patterns.
Alfred, Find the Attacker - A Primer on AI and ML Applications in the IT Security Domain
Explore AI and ML applications in IT security, covering classification, outlier detection, and user behavior analysis for enhanced protection and threat detection.
Spike Detection in Alert Correlation at LinkedIn
Discover how LinkedIn uses spike detection in alert correlation to quickly identify root causes of outages in their complex microservices architecture, reducing false positives and engineer toil.
Practical Cyborgism - Machine Learning for Bro Logs
Explore machine learning techniques for analyzing Bro logs, focusing on supervised and unsupervised methods to enhance cybersecurity threat detection and analysis.
Production ML Monitoring - Outliers, Drift, Explainers & Statistical Performance
Practical deep dive into advanced ML monitoring techniques, covering outliers, drift, explainers, and statistical performance for robust production deployment and scalability.
Data Preprocessing and Feature Engineering for Machine Learning
Master data preprocessing and feature engineering techniques for effective machine learning. Explore imputation, encoding, transformations, and more to maximize value from your data and improve model performance.
Distance Metric Learning and Outlier Detection in Data Mining - Spring 2023
Delve into advanced data mining concepts, focusing on distance metric learning, outlier detection techniques, and practical applications of DBSCAN for effective data analysis.
An Introduction to Drift Detection
Explore drift detection in machine learning, covering types, detection methods, and practical applications using Alibi Detect. Gain hands-on experience with real-world examples and state-of-the-art techniques.
Robust Parameter Estimation in Computer Vision
Explore robust parameter estimation in computer vision, focusing on algorithms for handling outliers in large-scale data and recent developments in the field.
Black Hat USA 2025
Black Hat USA 2025