Using #ApacheSpark ML and #TensorFlow AI with AWS's new, standards-based Jupyter notebook and distributed job scheduler called SageMaker @Databricks killer? Definitely less clunky and proprietary than Databricks. https://lnkd.in/eenYiyT
Ferris Jumah
8y
Cool stuff. Any thoughts on Google Cloud? I've migrated all of my machine learning pipelines to Google Cloud Platform over the past year, which already has this technology, precisely because of how clunky the AWS ecosystem is.
Thanks for sharing. Can you share your experience on what clunkiness of Databricks Sagemaker solves?
1 click training to production with ML EC2 instance and API end point.. wow. This is powerful stuff for life adaptation of ML powered apps.
Roy Ben-Alta
8y
Happy to hear your thoughts on sagemaker Chris. Happy to hear feedback and share with our eng team
late comer. IBM Data Science Experience had an early gain!
Thanks for sharing!
Kevin Diependaele