GCP: Complete Google Data Engineer and Cloud Architect Guide
- 4.3
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Brief Introduction
The Google Cloud for ML with TensorFlow, Big Data with Managed HadoopDescription
This course is a really comprehensive guide to the Google Cloud Platform - it has ~25 hours of content and ~60 demos.
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)
Requirements
- Requirements
- Basic understanding of technology - superficial exposure to Hadoop is enough
Loony Corn
4.3 Raiting
GCP: Complete Google Data Engineer and Cloud Architect Guide
- 4.3
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