Credit card fraud detection has emerged as a critical challenge in modern financial transactions due to the increasing prevalence of online transactions and digital payment methods. The unauthorized use of credit cards for fraudulent activities poses substantial financial risks to individuals, businesses, and financial institutions. To combat this issue, sophisticated fraud detection systems are required to swiftly identify and prevent fraudulent transactions, ensuring the security and trustworthiness of financial operations. This project aims to develop a credit card fraud detection system using machine learning algorithms and advanced analytics techniques. The system will analyze transaction data in real-time to identify potentially fraudulent activities and alert users or financial institutions to take appropriate actions.

Heart disease is the #2 cause of death in Malaysia (DOSM, 2022), and 1 in 5 heart attack patients are younger than 40s. So, early detection of heart disease is very important to reduce the mortality rate. Dataset: This dataset describes the contents of the heart-disease diagnosis. - Data Source: UCI Machine Learning Repository - Data URL: https://archive.ics.uci.edu/dataset/45/heart+disease Check it out here for interactive notebook: https://colab.research.google.com/drive/1oTTgcuzR6jFtnBGBHRrAvNhJ_uNWOzP0?usp=sharing for this prediction model. If you wish to my other content, please feel free to visit my blog at https://tanyongsheng.net/blog/