Challenge – Credit Fraud Detection
In this Summer Machine Learning Lab you and your team will work together to solve a Credit Fraud Detection problem, using a dataset with realcredit card transactions.
The dataset consists of 284,807 transactions, with only numerical features, that are anonymized due to confidentiality issues.
The transactions can be fraudulent or not, making this a binary classification problem.
Your objective will be to apply Machine Learning techniques to develop classifiers capable of successfully predicting fraudulent
You will use the Azure Machine Learning Studio, a cloud GUI-based integrated development environment for developing and deploying Machine Learning Solutions.
Our words on this lab
Because research needs to happen first at the labs and not at the customer site, we built this to improve our products and services to our customers.
Redatasense is just the result of this philosophy.
CEO @ LINK REDGLUE
It is a great challenge to build and accelerate a lab that will provide A.I and ML solutions for Redglue end customers.