UDEMY 2021 - GCP: Complete Google Data Engineer and Cloud Architect Guide

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The Google Cloud for ML with TensorFlow, Big Data with Managed Hadoop

You can find "Download Link" as a button at the end of this article.

What you’ll learn

  • Deploy Managed Hadoop apps on the Google Cloud
  • Build deep learning models on the cloud using TensorFlow
  • Build deep learning models on the cloud using TensorFlow

  • Make informed decisions about Containers, VMs and AppEngine
  • Make informed decisions about Containers, VMs and AppEngine

  • 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! Anyone looking to use the Google Cloud Platform in their organizations
  • Yep! Any one who is interesting in architecting compute, networking, loading balancing and other solutions using the GCP
  • Yep! Any one who wants to deploy serverless analytics and big data solutions on the Google Cloud
  • Yep! Anyone looking to build TensorFlow models and deploy them on the cloud
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