The Google Cloud for ML with TensorFlow, Big Data with Managed Hadoop
What you'll learn
Deploy Managed Hadoop apps on the Google Cloud
Use big data technologies such as BigTable, Dataflow, Apache Beam and Pub/Sub
Requirements
Basic understanding of technology - superficial exposure to Hadoop is enough
Description
The Google Cloud Platform is not currently the most popular cloud offering out there - that's AWS of course - but it is possibly the best cloud offering for high-end machine learning applications. That's because TensorFlow, the super-popular deep learning technology is also from Google.
What's Included:
Compute and Storage - AppEngine, Container Enginer (aka Kubernetes) and Compute Engine
Big Data and Managed Hadoop - Dataproc, Dataflow, BigTable, BigQuery, Pub/Sub
TensorFlow on the Cloud - what neural networks and deep learning really are, how neurons work and how neural networks are trained.
DevOps stuff - StackDriver logging, monitoring, cloud deployment manager
Security - Identity and Access Management, Identity-Aware proxying, OAuth, API Keys, service accounts
Networking - Virtual Private Clouds, shared VPCs, Load balancing at the network, transport and HTTP layer; VPN, Cloud Interconnect and CDN Interconnect
Hadoop Foundations: A quick look at the open-source cousins (Hadoop, Spark, Pig, Hive and HBase)
Who this course is for:
Yep! Any one who wants to deploy serverless analytics and big data solutions on the Google Cloud


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