Credit Card Frauds Detection is a very complex topic. Banks are trying to use advanced analytical techniques to catch them. Many Frauds are happening everyday and criminals are always innovating to always get new victims. Most of the times, they steal the credit cards information to make a lot of online purchases. They can only be detected when the victim notices some unusual buying in his bank account.
How to catch them? What are the different types of credit card frauds? Why is it important to have all the data centralized in one place to be able to catch them? Should you use Real-time or Near Real-time analytics? We will answer to those questions and even more.
Hands-on: We will implement a Random Forest Classifier model to detect Credit Card Fraud. We will use interesting predictors like Moving Windows and Advanced Analytical Functions to compute ZSCORES.
Chapters:
0:00 Intro
0:58 Definition
1:24 Different Fraud Types
1:59 Phishing
2:38 Hacking
3:24 With & Without Machine Learning
5:45 How to detect frauds?
7:13 Near Real-Time or Real-Time
9:28 Features Engineering
10:25 Hands-on
17:23 Thank-you
VerticaPy Installation Guide: [ Ссылка ]
Notebook: [ Ссылка ]
Dataset: [ Ссылка ]
Presenter: Badr Ouali
VerticaPy Website: [ Ссылка ]
LinkedIN: [ Ссылка ]
Music: [ Ссылка ] - Creative Minds
Photos: [ Ссылка ]
software: #verticapy #vertica
topics: #outliers #bias #fraud #anomaly #detection #credit #card #phishing #hacking
