Anomaly Detection in Machine Learning | Gaussian Distribution Explained (Step-by-Step)
In this video, you will learn Anomaly Detection in Machine Learning using the Gaussian Distribution (Normal Distribution) approach. This lecture explains how density estimation is used to detect unusual or abnormal data points in unlabeled datasets, a key concept in unsupervised learning.
We cover:
What is Anomaly Detection
Why Gaussian Distribution is used
Modeling p(x) using independent features
Mean (μ) and Variance (σ²) estimation
Probability calculation for new examples
How to choose epsilon (ε) for anomaly decision
Real-world examples like aircraft engine fault detection and fraud detection
👍 If you find this helpful, like, share, and subscribe for more ML & AI tutorials.
💬 Follow & Connect
GitHub Repository:https://github.com/dr-mushtaq/Machine...
Enroll Full Course: https://coursesteach.com/
Whatsapp Group:https://chat.whatsapp.com/L9URPRThBEa...
#AnomalyDetection #MachineLearning #GaussianDistribution #DensityEstimation #UnsupervisedLearning
#DataScience #AI #AndrewNg #MLAlgorithms #ArtificialIntelligence #NormalDistribution #MLTutorial #DeepLearningBasics
#ComputerScience