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Google Cloud Solutions II: Data and Machine Learning

Expert 5 pasos 5 horas 29 créditos

In this advanced-level quest, you will learn how to harness serious Google Cloud computing power to run big data and machine learning jobs. The hands-on labs will give you use cases, and you will be tasked with implementing big data and machine learning practices utilized by Google’s very own Solutions Architecture team. From running Big Query analytics on tens of thousands of basketball games, to training TensorFlow image classifiers, you will quickly see why Google Cloud is the go-to platform for running big data and machine learning jobs.

Infrastructure Application Development Business Transformation Machine Learning

Requisitos previos:

This Quest expects solid hands-on proficiency with Google Cloud workflows and processes, especially those involving multiple services working together. It is recommended that the student have at least earned a Badge by completing the hands-on labs in the Quest. Additional experience with the labs in the Machine Learning APIs Quest will also be useful.

Quest Outline

Lab

Cómo explorar datos de la NCAA con BigQuery

Utilice BigQuery para explorar el conjunto de datos de la NCAA de jugadores, equipos y partidos de básquetbol. Los datos abarcan jugadas desde 2009 y anotaciones desde 1996. Mire Cómo la NCAA utiliza Google Cloud para aprovechar décadas de datos de deportes.

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Lab

TensorFlow for Poets

In this lab you will learn how to install and run TensorFlow on a single machine, then train a simple classifier to classify images of flowers.

Lab

Creating an Object Detection Application Using TensorFlow

This lab will show you how to install and run an object detection application. The application uses TensorFlow and other public API libraries to detect multiple objects in an uploaded image.

Lab

Using OpenTSDB to Monitor Time-Series Data on Cloud Platform

In this lab you will learn how to collect, record, and monitor time-series data on Google Cloud Platform (GCP) using OpenTSDB running on Google Kubernetes Engine and Google Cloud Bigtable.

Lab

Scanning User-generated Content Using the Cloud Video Intelligence and Cloud Vision APIs

This lab will show you how to deploy a set of Cloud Functions in order to process images and videos with the Cloud Vision API and Cloud Video Intelligence API.

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