Artificial Intelligence Conference San Francisco 108/114
Mary Wahl
Data Scientist II, Microsoft Corporation
Mary Wahl is a member of Microsoft’s Boston Algorithms and Data Science team, which develops custom machine learning solutions for enterprise customers. Previously, Mary studied recent human migration, disease risk estimation, and forensic reidentification using crowdsourced genomic and genealogic data at the Whitehead Institute at Columbia University under Yaniv Erlich.
Sessions
4:50pm–5:30pm Tuesday, September 19, 2017
Scalable operationalization of trained CNTK and TensorFlow DNNs
Implementing AI
Location: Imperial B
Location: Imperial B
Level: Intermediate
Secondary topics: Technical best practices, Tools and frameworks
Mary Wahl (Microsoft Corporation)
Mary Wahl shares a cloud-based Hadoop ecosystem solution for deploying deep neural networks (DNNs) with scalable compute resources to accommodate changing workloads and demonstrates how to apply trained Microsoft CNTK and TensorFlow DNNs to a large image set on an HDFS (Azure Data Lake Store) using the Python bindings for these deep learning frameworks and a Microsoft HDInsight Spark cluster.
