Head, Artificial Intelligence and Machine Learning R&D
Saratendu Sethi is Head of Artificial Intelligence and Machine Learning R&D at SAS Institute. He leads SAS’ software development and research teams for Artificial Intelligence, Machine Learning, Cognitive Computing, Deep Learning, and Text Analytics. Saratendu has extensive experience in building global R&D teams, launching new products and business strategies. Perennially fascinated by how technology enables a creative life, he is a staunch believer in transforming powerful algorithms into innovative technologies. At SAS, his teams develop machine learning, cognitive- and semantic-enriched capabilities for unstructured data and multimedia analytics. He joined SAS Institute through the acquisition of Teragram Corporation, where he was responsible for the development of natural language processing and text analytics technologies. Before joining Teragram, Saratendu held research positions at the IBM Almaden Research Center and at Boston University, specializing in computer vision, pattern recognition, and content-based search.
By This Author
Machine Learning with SAS®: Special Collection
Foreword by Saratendu Sethi
Machine learning is a branch of artificial intelligence (AI) that develops algorithms that allow computers to learn from examples without being explicitly programmed. Machine learning identifies patterns in the data and models the results. These descriptive models enable a better understanding of the underlying insights the data offers. Machine learning is a powerful tool with many applications, from real-time fraud detection, the Internet of Things (IoT), recommender systems, and smart cars. It will not be long before some form of machine learning is integrated into all machines, augmenting the user experience and automatically running many processes intelligently.
SAS offers many different solutions to use machine learning to model and predict your data. The papers included in this special collection demonstrate how cutting-edge machine learning techniques can benefit your data analysis.