14–17 Oct 2019

Ahmed Menshawy
Machine Learning Engineer, Mastercard Labs

Ahmed Menshawy is a machine learning engineer in the AI Practice within the R&D Group at Mastercard Labs, where he works on a wide range of problems related to the application of AI and machine learning to Mastercard’s products and services. Ahmed is interested in studying the overlap between knowledge, logic, language, and learning. In particular, his focus is in how machine learning can be used for distilling large amounts of unstructured, semistructured, and structured data with hidden patterns into new knowledge about the world by using methods ranging from deep learning to statistical relational learning. Ahmed has authored two books, Deep Learning with TensorFlow and Deep Learning by Example, which focus on advanced deep learning topics. Ahmed has a BSc in computer science and an MSc in machine learning from Helwan University, Cairo, Egypt.

Sessions

11:05–11:45 Wednesday, 16 October 2019

Location: King's Suite - Balmoral

Developing a modern, open source machine learning pipeline with Kubeflow

Implementing AI

Steve Flinter (Mastercard Labs), Ahmed Menshawy (Mastercard Labs)

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Steve Flinter and Ahmed Menshaw explore the work that Mastercard Labs undertook to build an end-to-end machine learning pipeline, suitable for both R&D and production, using Kubernetes and Kubeflow. They demonstrate how the pipeline can be defined, configured, connected to a data streaming service, and used to train and deploy a model, which can be exposed for inference via an API. Read more.