Google Cloud/Scientific Data Processing: Difference between revisions
From charlesreid1
No edit summary |
No edit summary |
||
| (One intermediate revision by the same user not shown) | |||
| Line 1: | Line 1: | ||
{{Main|Google Cloud/Review}} | |||
Multi-part tutorial for running a scientific data processing pipeline. | Multi-part tutorial for running a scientific data processing pipeline. | ||
| Line 20: | Line 22: | ||
[[Google Cloud/Coastline Classification Tensorflow CloudML]] | [[Google Cloud/Coastline Classification Tensorflow CloudML]] | ||
==Flags== | |||
[[Category:Google Cloud]] | |||
[[Category:Data Engineering]] | |||
[[Category:January 2018]] | |||
[[Category:2018]] | |||
Latest revision as of 22:27, 8 January 2018
Main article: Google Cloud/Review
Multi-part tutorial for running a scientific data processing pipeline.
Topics:
- Weather Data in BigQuery
- Apache Spark for Image Processing using Spark and Dataproc
- Image Processing Pipeline using Beam and Dataproc
- Analyzing BigQuery Data with Datalab
- Predicting Baby Weight with Tensorflow on CloudML Engine
- Image Classification of Coastlines using Tensorflow on CloudML Engine
Pages:
Google Cloud/Weather Data in BigQery - analyzing historical weather data and other data using BigQuery
Google Cloud/Image Processing Pipeline
Google Cloud/Baby Weight Tensorflow CloudML
Google Cloud/Coastline Classification Tensorflow CloudML