Скачать или смотреть #151

Videos #154 to #159 provide coding sessions using the Anomaly Detection algorithms that we learned: Local Outlier Factor (LOF), One Class SVM and Isolation Forest. We will compare their performance with the best classifiers that (shallow) Machine Learning has to offer: Random Forest and XGboost. Performance Metric will be ROC Curve and AUC.

As usual we will be using Colab and Python. We will also use pyOD. The dataset that we will use is the credit card fraud dataset: https://www.kaggle.com/isaikumar/cred...

This video is part of a comprehensive tutorial on AI, Machine Learning and Deep Learning.
Course notes of this tutorial can be found on: GitHub:https://github.com/mfavaits/YouTube-S...

The course was inspired by videos of Andrew Ng, Kilian Weinberger and the book of Francois Chollet: Deep Learning with Python.