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Applica le tue competenze nella console Google Cloud

Vinisha Shukla

Membro dal giorno 2019

Campionato Argento

1700 punti
Intermediate ML: TensorFlow on Google Cloud Earned ago 18, 2019 EDT
VM Migration Earned ago 17, 2019 EDT
Introduzione al ML: elaborazione del linguaggio Earned ago 16, 2019 EDT
Intro to ML: Image Processing Earned ago 16, 2019 EDT
Baseline: dati, ML, AI Earned ago 13, 2019 EDT
Machine Learning APIs Earned ago 12, 2019 EDT
DEPRECATED Google Cloud Solutions II: Data and Machine Learning Earned ago 11, 2019 EDT
DEPRECATED Cloud Architecture Earned ago 11, 2019 EDT
Kubernetes in Google Cloud Earned ago 10, 2019 EDT
Conoscenze di base: infrastruttura Earned ago 3, 2019 EDT
Google Developer Essentials Earned ago 2, 2019 EDT
Google Cloud Essentials Earned lug 21, 2019 EDT

TensorFlow is an open source software library for high performance numerical computation that's great for writing models that can train and run on platforms ranging from your laptop to a fleet of servers in the Cloud to an edge device. This quest takes you beyond the basics of using predefined models and teaches you how to build, train and deploy your own on Google Cloud.

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Google Cloud’s four step structured Cloud Migration Path Methodology provides a defined and repeatable path for users to follow when migrating and modernizing Virtual Machines. In this quest, you will get hands-on practice with Google’s current solution set for VM assessment, planning, migration, and modernization. You will start by analyzing your lab environment and building assessment reports with CloudPhysics and StratoZone, then build a landing zone within Google Cloud leveraging Terraform’s infrastructure-as-code templates, next you will manually transform a two-tier application into a cloud-native workload running on Kubernetes, and finally, transform a VM workload into Kubernetes with Migrate for Anthos and migrate a VM between cloud environments.

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Non è un segreto che il machine learning sia uno dei campi in più rapida crescita nel settore tecnologico e la piattaforma Google Cloud è stata fondamentale per promuoverne lo sviluppo. Con le numerose API, Google Cloud dispone di uno strumento adeguato praticamente per qualsiasi job di machine learning. In questo corso introduttivo, farai pratica con il machine learning applicato all'elaborazione del linguaggio naturale partecipando ai lab che ti consentiranno di estrarre entità da un testo ed eseguire analisi del sentiment e della sintassi, nonché utilizzare l'API Speech-to-Text per la trascrizione.

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Using large scale computing power to recognize patterns and "read" images is one of the foundational technologies in AI, from self-driving cars to facial recognition. The Google Cloud Platform provides world class speed and accuracy via systems that can utilized by simply calling APIs. With these and a host of other APIs, GCP has a tool for just about any machine learning job. In this introductory quest, you will get hands-on practice with machine learning as it applies to image processing by taking labs that will enable you to label images, detect faces and landmarks, as well as extract, analyze, and translate text from within images.

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Big data, machine learning e intelligenza artificiale sono i principali argomenti di computing trattati attualmente, ma questi campi sono piuttosto specializzati ed è complicato reperire materiale introduttivo. Fortunatamente, Google Cloud offre servizi facili da usare in queste aree e con questo corso di livello introduttivo, in modo da poter fare i primi passi con strumenti come BigQuery, API Cloud Speech e Video Intelligence.

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It's no secret that machine learning is one of the fastest growing fields in tech, and Google Cloud has been instrumental in furthering its development. With a host of APIs, Google Cloud has a tool for just about any machine learning job. In this advanced-level course, you will get hands-on practice with machine learning APIs by taking labs like Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? Enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.

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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.

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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Cloud Architect Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.

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Kubernetes è il sistema di orchestrazione dei container più diffuso e Google Kubernetes Engine è stato progettato specificamente per supportare i deployment Kubernetes gestiti in Google Cloud. In questo corso di livello avanzato, potrai esercitarti nella configurazione di immagini e container Docker e nel deployment di applicazioni Kubernetes Engine complete. Grazie a questo corso, apprenderai le competenze pratiche necessarie per integrare l'orchestrazione dei container nel tuo workflow. Stai cercando un Challenge Lab pratico per dimostrare le tue abilità e convalidare le tue conoscenze? Dopo aver completato questo corso, termina il Challenge Lab aggiuntivo alla fine del corso Esegui il deployment di applicazioni Kubernetes su Google Cloud per ricevere un esclusivo badge digitale Google Cloud.

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Se sei uno sviluppatore cloud principiante che vuole fare ancora pratica Google Cloud Essentials, questo corso fa al caso tuo. Acquisirai esperienza pratica attraverso lab specifici su Cloud Storage e altri servizi per applicazioni chiave come Monitoring e Cloud Functions. Svilupperai competenze preziose applicabili a qualsiasi iniziativa Google Cloud.

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This introductory-level quest shows application developers how the Google Cloud ecosystem could help them build secure, scalable, and intelligent cloud native applications. You learn how to develop and scale applications without setting up infrastructure, run data analytics, gain insights from data, and develop with pre-trained ML APIs to leverage machine learning even if you are not a Machine Learning expert. You will also experience seamless integration between various Google services and APIs to create intelligent apps.

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In this introductory-level course, you get hands-on practice with the Google Cloud’s fundamental tools and services. Optional videos are provided to provide more context and review for the concepts covered in the labs. Google Cloud Essentials is a recommendeded first course for the Google Cloud learner - you can come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.

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