Discover the power of machine learning in combating fraud with our upcoming webinar on "Fraud Detection using Machine Learning." In this engaging session, industry experts will guide you through the essentials of machine learning technologies and their pivotal role in identifying and preventing fraudulent activities more effectively than traditional approaches. Understand the challenges in fraud detection, the variety of machine learning models applied, and explore real-world success stories. This session is for anyone looking to deepen their knowledge of machine learning applications.
Agenda for the session
- Introduction to Machine Learning in Fraud Detection
- Machine Learning Models and Challenges
- Data Science & Machine Learning Program by MIT IDSS
- Live Q&A
About Speakers
Anuj Saboo
Data Scientist, BAT, Canada
Anuj Saboo, currently working as a Data Scientist at BAT Canada, is a data practitioner with 7+ years of industry experience in developing data-focused solutions using Big Data Engineering, Analytics, Machine Learning, and Natural Language Processing transforming data at rest to data in action.
Data Science and Machine Learning: Making Data-Driven Decisions Program
The Data Science and Machine Learning: Making Data-Driven Decisions Program has a curriculum carefully crafted by MIT faculty to provide you with the skills & knowledge to apply data science techniques to help you make data-driven decisions.
This data science program has been designed for the needs of data professionals looking to grow their careers and enhance their data science skills to solve complex business problems. In a relatively short period of time, the program aims to build your understanding of most industry-relevant technologies today such as machine learning, deep learning, network analytics, recommendation systems, graph neural networks, and time series.
