Server Computers (AD Ex.)
dataset: thoroughput & latency
Implementation detail: Mean Normalization
- By now, we already have quite a grasp about the Recommendation System and Collaboration Filtering algoirthm
Vectorization: Low Rank Matrix Factorization
- in the last video, we talked about Collaboration Filtering Algorithm
Content-based Recommendation
- in the last video, we are addressing Recommender Systems problem that have set of movies and set of users and the problem is try to recommend movies they never seen, how they would rate it
Problem Formulation
- Recommender System is one of the most important application in Machine Learning.
Choosing what features to use
- In previous video, we have implemented a system that can make Anomaly Detection and evaluate it
Anomaly Detection vs Supervised Learning
- By now we already knew that we can evaluate Anomaly Detection by label the data whether is normal(y = 0) or anomalous(y = 1)
Developing and evaluating an anomaly detection system
- In this video we're going to implement specific application for Anomaly Detection
Algorithm
- The Algorithm on how to Implement Gaussian Distribution for Anomaly Detection
Gaussian Distribution
- Gaussian/Normal Distribution