Credit Card Fraud Detection-Data Science Projects
In this project tutorial, we will be predicting whether a particular transaction is a Fraudulent transaction or Genuine transaction. We will be dealing with data imbalance with the help of upsampling and downsampling using resample and SMOTE. We will dive into the BFSI industry, i.e. Banking, Financial Services, and the Insurance Industry.
We will be using different algorithms and models to arrive at our answer. Example:
Logistic Regression,
Support Vector Machine,
Random Forest Classifier,
Naive Bayes,
GridSearchCV,
AUC
Before we start, please note that this tutorial is part of the Data Science Project Mastery Program, which is a practical hands-on data science tutorial for anyone to learn data science right from the basics to advance by building projects and great Data Science Portfolio. Feel free to check it out.
In order for you to make the best out of this tutorial, I have put this tutorial in the form of a video for better understanding
Watch and work along
INTRODUCTION
PART 1
PART 2
GOOD LUCK
If you are interested in learning Data Science, the right way, I advise you to start with this course that focuses on teaching and building end-to-end data science projects.
I will also be posting more FREE Data Science Projects on the Youtube Channel, so don’t forget to subscribe and hit the notification bell to get notified anytime I post them.
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