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Full notes at ocdevel.com/mlg/14
Anomaly Detection Systems
- Applications: Credit card fraud detection and server activity monitoring.
- Concept: Identifying outliers on a bell curve.
- Statistics: Central role of the Gaussian distribution (normal distribution) in detecting anomalies.
- Process: Identifying significant deviations from the mean to detect outliers.
Recommender Systems
- Types:
- Content Filtering: Uses features of items (e.g., Pandora’s Music Genome Project).
- Collaborative Filtering: Based on user behavior and preferences, like "Users Also Liked" model utilized in platforms like Netflix and Amazon.
- Applications in Machine Learning: Linear regression applications in recommender systems for predicting user preferences.
Markov Chains
- Explanation: Series of states with probabilities dictating transitions to next states; present state is sufficient for predicting next state (Markov principle).
- Use Cases: Often found in reinforcement learning and operations research.
- Monte Carlo Simulation: Running simulations to determine the expected value or probable outcomes of Markov processes.
Resource
- Andrew NG's Coursera Course - Week 9: Focuses on anomaly detection and recommender systems.