Detecting anomalous patterns in data can lead to significant actionable insights in a wide variety of application domains, such as fraud detection, network traffic management, predictive healthcare, energy monitoring and many more.
However, detecting anomalies accurately can be difficult. What qualifies as an anomaly is continuously changing and anomalous patterns are unexpected. An effective anomaly detection system needs to continuously self-learn without relying on pre-programmed thresholds.
Join our speakers Ravishankar Rao Vallabhajosyula, Senior Data Scientist, Impetus Technologies and Saurabh Dutta, Technical Product Manager - StreamAnalytix, in a discussion on:
Senior Data Scientist, Impetus Technologies
Ravi is a Senior Data Scientist at Impetus Technologies. He leads the data science practice team in the US and works closely with clients, program managers and other IT teams to turn complex data into critical information and knowledge that can be used to make data-driven business decisions. Ravi plays an instrumental role in architecting end-to-end ML-driven products/solutions and getting them live into production. He also has extensive experience working with large sets of data to establish accurate and scalable analytics systems across varied applications. His areas of expertise relevant to anomaly detection includes machine learning, natural language processing, data mining, artificial intelligence, graph analytics and big data technologies.
Technical Product Manager, StreamAnalytix
Saurabh is a Technical Product Manager at StreamAnalytix where he leads multiple engineering and R&D efforts. He is one of the early team members who bootstrapped StreamAnalytix. He is responsible for analyzing complex engineering and business challenges for clients, managing and developing a roadmap and providing an appropriate solution which can be incorporated in the product. He brings a unique blend of business acumen and technical knowledge that help clients achieve their objectives. His areas of expertise include big data, advanced analytics and cloud computing.