Presented By O’Reilly and Cloudera
Make Data Work
March 5–6, 2018: Training
March 6–8, 2018: Tutorials & Conference
San Jose, CA
Chris Fregly

Chris Fregly
Developer Advocate, AI and Machine Learning, Amazon Web Services

Website | @cfregly

Chris Fregly is a senior developer advocate focused on AI and machine learning at Amazon Web Services (AWS). Chris shares knowledge with fellow developers and data scientists through his Advanced Kubeflow AI Meetup and regularly speaks at AI and ML conferences across the globe. Previously, Chris was a founder at PipelineAI, where he worked with many startups and enterprises to deploy machine learning pipelines using many open source and AWS products including Kubeflow, Amazon EKS, and Amazon SageMaker.

Sessions

2:40pm–3:20pm Thursday, March 8, 2018
Building ML and AI pipelines with Spark and TensorFlow
Big data and data science in the cloud, Data engineering and architecture, Data science and machine learning, Streaming systems and real-time applications
 Location: Expo Hall 1
Secondary topics:  Expo Hall
Chris Fregly (Amazon Web Services)
Average rating: *****
(5.00, 1 rating)
Chris Fregly demonstrates how to extend existing Spark-based data pipelines to include TensorFlow model training and deploying and offers an overview of TensorFlow’s TFRecord format, including libraries for converting to and from other popular file formats such as Parquet, CSV, JSON, and Avro stored in HDFS and S3. Read more.