Building predictive models requires time, effort, and knowledge of algorithms to create effective systems that can predict the outcome accurately. With that being said, IBM has introduced AutoAI, which automates all of the tasks involved in building predictive models for different requirements.

Join IBM Developer to learn more about how AutoAI can churn out great models quickly, which saves time and effort and aids in a faster decision-making process! In this webinar, we focus on building systems for churning out predictions that can be used in different scenarios. We try to predict fraudulent transactions that we know can reduce monetary loss and risk mitigation. The same approach can be used for other scenarios like predicting customer churn or demand and supply forecast.

Create your IBM Cloud Account at http://ibm.biz/fraudprediction

Bedang Sen is a Developer Advocate part of the IBM Developer Advocacy Team in Dubai. He has development experience in C/C++, Java, Python, and JavaScript. Bedang is passionate about Data Science, Artificial Intelligence and Cybersecurity and aims to leverage these technologies together to solve current world issues. He enjoys spending his free time taking part in hackathons and developing and pitching proof of concepts. As a Developer Advocate, he also acts as a technical mentor in hackathons and conducts workshops for their benefit.

Fraud Prediction using AutoAI