MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch

Genre: eLearning | Language: English | Duration: 25 lectures (5h 18m) | Size: 1.55 GB

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