Machine learning enables computers to learn from large amounts of data without being explicitly programmed to do so. Deep learning is a sub-field of machine learning that has led to breakthroughs in several artificial intelligence tasks, achieving state-of-the-art performance in computer vision, speech recognition, and natural language processing.
Not surprisingly, many companies are looking for ways to start applying machine learning and deep learning to their business processes and data assets to realize the vision of an Intelligent Enterprise. As the world’s most relevant enterprise data is part of SAP’s system and business network, SAP aspires to make all its enterprise solutions intelligent and help customers leverage their data.
The objective of this course is to introduce SAP Leonardo Machine Learning Foundation, which is a platform for machine learning and data science that allows customers, partners, and SAP to build intelligent applications. To get an understanding of the capabilities of this innovative technology, new business applications and use cases for enterprise machine learning are presented.
SAP Leonardo Machine Learning Foundation supports several capabilities for developers and data scientists – from using customizable functional services for text, image, and speech processing, to training and deploying own deep learning models for usage in Intelligent Enterprise applications.
Unit 1: SAP Leonardo Machine Learning
Unit 2: SAP Leonardo Machine Learning Foundation Capabilities
Unit 3: Intelligent Enterprise Applications
Unit 4: Business Use Cases for Enterprise Machine Learning
Unit 5: Ready-to-Use Functional Services
Unit 6: Consumption, Customizable Services, and Bring-Your-Own-Model
Unit 7: SAP Leonardo Machine Learning Foundation Roadmap
Dr. Matthias Sessler leads the technical enablement for SAP Leonardo Machine Learning Foundation. His vision is to enable customers, partners, and internal development teams to make enterprise applications intelligent.
Matthias previously held different positions in pre-sales, development, and product management in the SAP technology area. He also worked as a lecturer in digital technology and computer architecture at DHBW Mosbach.
Matthias earned his Ph.D. at CERN in collaboration with the University of Heidelberg, where he developed pattern recognition algorithms for finding the Higgs boson.
Dieser Kurs wurde vom 25. September 2018 bis 5. Dezember 2018 gehalten.
Am ersten Tag dieses Kurses waren 15323 Teilnehmer eingeschrieben.
Bis zur Abschlussarbeit hat sich diese Zahl auf 23596 erhöht.
28635 Teilnehmer eingeschrieben.
Der Kurs wurde mit durchschnittlich 4.35 Sternen bei 3037 abgegebenen Stimmen bewertet.
Mehr Informationen finden Sie in den Richtlinien für Leistungsnachweise.
Dr. Karthik Muthuswamy is a data scientist for ML Sales and Services at SAP. He works on researching and developing services that leverage machine learning to enable the development of Intelligent Enterprise applications and, is an active proponent of human-centered machine learning.
Karthik has used machine learning for developing applications such as guiding autonomous vehicles, sentence comprehending bots, among many others. He gives talks and conducts workshops on machine learning for the developer community to reduce the barriers of entry to developing applications that use machine learning.