This document discusses Amazon's machine learning services for building conversational interfaces and extracting insights from unstructured text and audio. It describes Amazon Lex for creating chatbots, Amazon Comprehend for natural language processing tasks like entity extraction and sentiment analysis, and how they can be used together for applications like intelligent call centers and content analysis. Pre-trained APIs simplify adding machine learning to apps without requiring ML expertise.
Dal riconoscimento facciale al riconoscimento di frodi o difetti di fabbricazione, l'analisi di immagini e video che sfruttano tecniche di intelligenza artificiale, si stanno evolvendo e raffinando a ritmi elevati. In questo webinar esploreremo le possibilità messe a disposizione dai servizi AWS per applicare lo stato dell'arte delle tecniche di computer vision a scenari reali.
AWS offers a family of intelligent services that provide cloud-native machine learning and deep learning technologies to address different use cases and needs. This deck will help you to gain insight into practical use cases for Amazon Lex, Amazon Polly, and Amazon Rekognition, and learn about newly announced services Amazon Rekognition Video, Amazon Comprehend, Amazon Translate, and Amazon Transcribe. This presentation took place in Australia and New Zealand as part of the AWS Learning Series in 2018.
Journey to the cloud: a cosa deve pensare un’organizzazione che vuole migrare...Amazon Web Services
La complessità di un programma di cloud transformation che coinvolge la migrazione di centinaia o addirittura migliaia di server può essere una sfida importante per il program management e per il coordinamento dell’IT team incaricato del successo e del supporto di queste attività di preparazione e di migrazione. Questa sessione mette in luce il framework di AWS, altamente ripetibile e scalabile e il metodo che sta aiutando i clienti ad essere pronti per un’esecuzione accelerata della loro migrazione o la preparazione delle operazioni per i workload in esercizio da portare su AWS.
Building Modern Applications on AWS 2019 - Sydney
Building Modern Applications on AWS 2019 - Brisbane
Building Modern Applications on AWS 2019 - Melbourne
Amazon SageMaker Ground Truth: Build High-Quality and Accurate ML Training Da...Amazon Web Services
Successful machine learning models are built on high-quality training datasets. Labeling raw data to get accurate training datasets involves a lot of time and effort because sophisticated models can require thousands of labeled examples to learn from, before they can produce good results. Typically, the task of labeling is distributed across a large number of humans, adding significant overhead and cost. Join us as we introduce Amazon SageMaker Ground Truth, a new service that provides an effective solution to reduce this cost and complexity using a machine learning technique called active learning. Active learning reduces the time and manual effort required to do data labeling, by continuously training machine learning algorithms based on labels from humans. By iterating through ambiguous data points, Ground Truth improves the ability to automatically label data resulting in high-quality training datasets.
Level: 300
Speaker: Kris Skrinak - Partner Solutions Architect, ML Global Lead, AWS
Dal riconoscimento facciale al riconoscimento di frodi o difetti di fabbricazione, l'analisi di immagini e video che sfruttano tecniche di intelligenza artificiale, si stanno evolvendo e raffinando a ritmi elevati. In questo webinar esploreremo le possibilità messe a disposizione dai servizi AWS per applicare lo stato dell'arte delle tecniche di computer vision a scenari reali.
AWS offers a family of intelligent services that provide cloud-native machine learning and deep learning technologies to address different use cases and needs. This deck will help you to gain insight into practical use cases for Amazon Lex, Amazon Polly, and Amazon Rekognition, and learn about newly announced services Amazon Rekognition Video, Amazon Comprehend, Amazon Translate, and Amazon Transcribe. This presentation took place in Australia and New Zealand as part of the AWS Learning Series in 2018.
Journey to the cloud: a cosa deve pensare un’organizzazione che vuole migrare...Amazon Web Services
La complessità di un programma di cloud transformation che coinvolge la migrazione di centinaia o addirittura migliaia di server può essere una sfida importante per il program management e per il coordinamento dell’IT team incaricato del successo e del supporto di queste attività di preparazione e di migrazione. Questa sessione mette in luce il framework di AWS, altamente ripetibile e scalabile e il metodo che sta aiutando i clienti ad essere pronti per un’esecuzione accelerata della loro migrazione o la preparazione delle operazioni per i workload in esercizio da portare su AWS.
Building Modern Applications on AWS 2019 - Sydney
Building Modern Applications on AWS 2019 - Brisbane
Building Modern Applications on AWS 2019 - Melbourne
Amazon SageMaker Ground Truth: Build High-Quality and Accurate ML Training Da...Amazon Web Services
Successful machine learning models are built on high-quality training datasets. Labeling raw data to get accurate training datasets involves a lot of time and effort because sophisticated models can require thousands of labeled examples to learn from, before they can produce good results. Typically, the task of labeling is distributed across a large number of humans, adding significant overhead and cost. Join us as we introduce Amazon SageMaker Ground Truth, a new service that provides an effective solution to reduce this cost and complexity using a machine learning technique called active learning. Active learning reduces the time and manual effort required to do data labeling, by continuously training machine learning algorithms based on labels from humans. By iterating through ambiguous data points, Ground Truth improves the ability to automatically label data resulting in high-quality training datasets.
Level: 300
Speaker: Kris Skrinak - Partner Solutions Architect, ML Global Lead, AWS
Driving AI Innovation with Machine Learning powered by AWS. AI is opening up new insights and efficiencies in enterprises of every industry. Learn how enterprises are using AWS’ machine learning capabilities combined with its deep storage, compute, analytics, and security services to deliver intelligent applications today. Strategies to develop ML expertise within your org will also be discussed.
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...Amazon Web Services
Per creare valore e costruire una propria offerta differenziante e riconoscibile, le startup di successo sanno come combinare tecnologie consolidate con componenti innovativi creati ad hoc.
AWS fornisce servizi pronti all'utilizzo e, allo stesso tempo, permette di personalizzare e creare gli elementi differenzianti della propria offerta.
Concentrandoci sulle tecnologie di Machine Learning, vedremo come selezionare i servizi di intelligenza artificiale offerti da AWS e, anche attraverso una demo, come costruire modelli di Machine Learning personalizzati utilizzando SageMaker Studio.
Enriching your app with Image recognition and AWS AI services Hebrew WebinarBoaz Ziniman
Artificial Intelligence services on the AWS cloud bring machine learning technologies such as image recognition and computer vision within reach of every developer.In this session, you will be introduced to AWS AI services for developers and learn how to use one of them, Amazon Rekognition, to add new capabilities to your applications.
High frequency enterprises embrace cloud computing as a flywheel for frequent value delivery. This requires tighter alignment with business unit stakeholders to increase agility and pace of innovation. In this session, we explore the potential for transformation that comes with cloud adoption and discuss how some of the world’s leading enterprises were able to transform and quickly deliver business value outcomes. We also explore organisational and technology best practices that you can implement to become a high frequency enterprise.
Which Internet of Things (IoT) network or platform will make the most of your data - now and in the long run? How do you keep your data secure in this connected world? Find out in our webinar, which tackles the infrastructure decisions that come with creating a smart place.
SKL208 - Turbocharge your Business with AI and Machine Learning - Tel Aviv Su...Boaz Ziniman
This session will focus on the basic building blocks of Artificial Intelligence (AI) and Machine Learning (ML) using AWS services. It will help you to identify use cases for ML with real-world examples, and help you create the right conditions for delivering successful ML-based solutions to your business.
How Different Large Organizations are Approaching Cloud AdoptionAmazon Web Services
The implementation of highly scalable, easy-to-deploy technology is transforming enterprises, but it’s not a one-size-fits-all approach. Organizations begin their cloud adoption journeys in many ways. Some start with pilot projects and others jump into mission-critical programs, but they are all starting with an existing infrastructure. Adopting cloud doesn’t mean scrapping it all and starting over. This session explores how organizations are using cloud while building on their existing technology and lessons they’ve learned along the way. In this session we will discuss when and how to leverage hybrid cloud computing to meet the needs of the enterprise. We will cover popular hybrid cloud use cases in enterprises, pillars to design a secure hybrid cloud environment and how to get started with AWS.
AWS Data-Driven Insights Learning Series_ANZ Sep 2019 Part 2Amazon Web Services
AWS has been supporting companies across Australia and New Zealand to put their most innovative tools and technologies to work to achieve their business needs and goals. AWS and our ecosystem of partners has helped the likes of CP Mining, IntelliHQ, WesCEF, Oz Minerals, Woodside and many more to modernise their analytics and data architecture in order to successfully generate business value from their data.
This event series aimed to educate customers with a broader understanding of how to build next-gen data lakes and analytics platforms and make connections with AWS.
Initiate Edinburgh 2019 - Top Cloud Security Myths DispelledAmazon Web Services
In this session, we cover the most common cloud security questions that we hear from customers. We provide detailed answers for each question, distilled from our practical experience working with organizations around the world. This session is for everyone who is curious about the cloud, cautious about the cloud, or excited about the cloud.
Previously, ETL meant using proprietary products with commercial databases and users with specialist skills. Learn how to create ETL data pipelines that can securely consume data at scale while using open source technologies and languages to enable your organisation, team, and data.
Speaker: Paul Macey, Big Data Specialist, AWS
Building a Customer-Centric Contact Center in a Regulated EnvironmentAmazon Web Services
This session will demonstrate how Amazon AI services enable Financial Services firms to deliver transformational customer experiences while still meeting regulatory obligations. Instead of human-intensive quality assurance and training processes, Amazon AI services provide data on customer sentiment and the most common issues raised during service interactions – all without the need to host any infrastructure, and while maintaining a scalable, elastic solution to align the cost of providing service with the demand.
Presenter: Kenneth Jackson, Global Account Solutions Architect, AWS and Hanybal Jajoo, Global Account Solutions Architect, AWS
Driving AI Innovation with Machine Learning powered by AWS. AI is opening up new insights and efficiencies in enterprises of every industry. Learn how enterprises are using AWS’ machine learning capabilities combined with its deep storage, compute, analytics, and security services to deliver intelligent applications today. Strategies to develop ML expertise within your org will also be discussed.
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...Amazon Web Services
Per creare valore e costruire una propria offerta differenziante e riconoscibile, le startup di successo sanno come combinare tecnologie consolidate con componenti innovativi creati ad hoc.
AWS fornisce servizi pronti all'utilizzo e, allo stesso tempo, permette di personalizzare e creare gli elementi differenzianti della propria offerta.
Concentrandoci sulle tecnologie di Machine Learning, vedremo come selezionare i servizi di intelligenza artificiale offerti da AWS e, anche attraverso una demo, come costruire modelli di Machine Learning personalizzati utilizzando SageMaker Studio.
Enriching your app with Image recognition and AWS AI services Hebrew WebinarBoaz Ziniman
Artificial Intelligence services on the AWS cloud bring machine learning technologies such as image recognition and computer vision within reach of every developer.In this session, you will be introduced to AWS AI services for developers and learn how to use one of them, Amazon Rekognition, to add new capabilities to your applications.
High frequency enterprises embrace cloud computing as a flywheel for frequent value delivery. This requires tighter alignment with business unit stakeholders to increase agility and pace of innovation. In this session, we explore the potential for transformation that comes with cloud adoption and discuss how some of the world’s leading enterprises were able to transform and quickly deliver business value outcomes. We also explore organisational and technology best practices that you can implement to become a high frequency enterprise.
Which Internet of Things (IoT) network or platform will make the most of your data - now and in the long run? How do you keep your data secure in this connected world? Find out in our webinar, which tackles the infrastructure decisions that come with creating a smart place.
SKL208 - Turbocharge your Business with AI and Machine Learning - Tel Aviv Su...Boaz Ziniman
This session will focus on the basic building blocks of Artificial Intelligence (AI) and Machine Learning (ML) using AWS services. It will help you to identify use cases for ML with real-world examples, and help you create the right conditions for delivering successful ML-based solutions to your business.
How Different Large Organizations are Approaching Cloud AdoptionAmazon Web Services
The implementation of highly scalable, easy-to-deploy technology is transforming enterprises, but it’s not a one-size-fits-all approach. Organizations begin their cloud adoption journeys in many ways. Some start with pilot projects and others jump into mission-critical programs, but they are all starting with an existing infrastructure. Adopting cloud doesn’t mean scrapping it all and starting over. This session explores how organizations are using cloud while building on their existing technology and lessons they’ve learned along the way. In this session we will discuss when and how to leverage hybrid cloud computing to meet the needs of the enterprise. We will cover popular hybrid cloud use cases in enterprises, pillars to design a secure hybrid cloud environment and how to get started with AWS.
AWS Data-Driven Insights Learning Series_ANZ Sep 2019 Part 2Amazon Web Services
AWS has been supporting companies across Australia and New Zealand to put their most innovative tools and technologies to work to achieve their business needs and goals. AWS and our ecosystem of partners has helped the likes of CP Mining, IntelliHQ, WesCEF, Oz Minerals, Woodside and many more to modernise their analytics and data architecture in order to successfully generate business value from their data.
This event series aimed to educate customers with a broader understanding of how to build next-gen data lakes and analytics platforms and make connections with AWS.
Initiate Edinburgh 2019 - Top Cloud Security Myths DispelledAmazon Web Services
In this session, we cover the most common cloud security questions that we hear from customers. We provide detailed answers for each question, distilled from our practical experience working with organizations around the world. This session is for everyone who is curious about the cloud, cautious about the cloud, or excited about the cloud.
Previously, ETL meant using proprietary products with commercial databases and users with specialist skills. Learn how to create ETL data pipelines that can securely consume data at scale while using open source technologies and languages to enable your organisation, team, and data.
Speaker: Paul Macey, Big Data Specialist, AWS
Building a Customer-Centric Contact Center in a Regulated EnvironmentAmazon Web Services
This session will demonstrate how Amazon AI services enable Financial Services firms to deliver transformational customer experiences while still meeting regulatory obligations. Instead of human-intensive quality assurance and training processes, Amazon AI services provide data on customer sentiment and the most common issues raised during service interactions – all without the need to host any infrastructure, and while maintaining a scalable, elastic solution to align the cost of providing service with the demand.
Presenter: Kenneth Jackson, Global Account Solutions Architect, AWS and Hanybal Jajoo, Global Account Solutions Architect, AWS
Artificial Intelligence (AI) services on the AWS cloud bring deep learning (DL) technologies like natural language understanding (NLU), automatic speech recognition (ASR), image recognition and computer vision (CV), text-to-speech (TTS), and machine learning (ML) within reach of every developer. In this session, you will be introduced to several new AI services: Amazon Lex, to build sophisticated text and voice chatbots; Amazon Rekognition, for deep learning-based image recognition; and Amazon Polly, for turning text into lifelike speech. The opportunities to apply one or more of these DL services are nearly boundless and this session will provide a number of examples and use cases to help you get started.
by Dario Rivera, Solutions Architect, AWS
Artificial Intelligence (AI) services on the AWS cloud bring deep learning (DL) technologies like natural language understanding (NLU), automatic speech recognition (ASR), image recognition and computer vision (CV), text-to-speech (TTS), and machine learning (ML) within reach of every developer. In this session, you will be introduced to several new AI services: Amazon Lex, to build sophisticated text and voice chatbots; Amazon Rekognition, for deep learning-based image recognition; and Amazon Polly, for turning text into lifelike speech. The opportunities to apply one or more of these DL services are nearly boundless and this session will provide a number of examples and use cases to help you get started.
Amazon AI services bring natural language understanding (NLU), automatic speech recognition (ASR), visual search and image recognition, text-to-speech (TTS), and ML technologies within the reach of every developer. In this session, we will dive deep into 2 specific AWS services: Amazon Lex and Amazon Polly. Amazon Lex uses the same technology as Amazon Alexa to provide advanced deep learning functionalities of automatic speech recognition (ASR) and natural language understanding (NLU) to enable you to build applications with conversational interfaces, commonly called chatbots. Amazon Polly is a service that turns text into lifelike speech. Polly lets you create applications that speak in over two dozen languages with a wide variety of natural sounding male and female voices to enable you to build entirely new categories of speech-enabled products.
AWS Summit Singapore - Building Tomorrow’s Bank with AI/ MLAmazon Web Services
Olivier Klein, Head of Emerging Technologies, APAC, AWS. AWS Customer Speakers:
Kyle McNamara, Executive General Manager, Program Management Office, National Australia Bank
Chye Kit Chionh, CEO, Cynopsis Solutions.
Machine learning is transforming how we interact with our customers and helps us make faster and better decisions within our business. Intelligent and continuously improving neural networks help to streamline written and spoken customer conversations, help improve customer service centers or ensure compliance within your organization. Deep Learning machine models are trained to automatically detect fraudulent activities or make best next action decisions. Attend this session to learn how machine learning is used in the financial service industry to improve operational excellence, compliance and improve customer experience. Furthermore learn from our customers NAB and Cynopsis Solutions how they drive digital insights, improve customer satisfaction across all digital channels and consolidate their data lakes to drive continuous ML efforts.
Hands-on with Rekognition, Polly & Lex - Pop-up Loft TLV 2017Amazon Web Services
The AWS Cloud now provides a range of AI services based on Deep Learning technology and automatic learning. These services bring natural language understanding (Amazon Lex), image recognition (Amazon Rekognition) and voice synthesis (Amazon Polly) to your applications. Come discover them during this session through a number of live demos.
An Introduction to the AI services at AWS - AWS Summit Tel Aviv 2017Amazon Web Services
Artificial Intelligence (AI) services on the AWS cloud bring deep learning (DL) technologies like natural language understanding (NLU), automatic speech recognition (ASR), image recognition and computer vision (CV), text-to-speech (TTS), and machine learning (ML) within reach of every developer. In this session, you will be introduced to several new AI services: Amazon Lex, to build sophisticated text and voice chatbots; Amazon Rekognition, for deep learning-based image recognition; and Amazon Polly, for turning text into lifelike speech. The opportunities to apply one or more of these DL services are nearly boundless and this session will provide a number of examples and use cases to help you get started.
Unlocking New Todays: Artificial Intelligence and Data Platforms on AWSAmazon Web Services
In this session, you will learn about our strategy for driving machine learning innovation for our customers and learn what’s new from AWS in the machine learning space. We will discuss and demonstrate the latest new services for ML on AWS: Amazon SageMaker, AWS DeepLens, Amazon Rekogntion Video, Amazon Translate, Amazon Transcribe, and Amazon Comprehend. Attend this session to understand how to make the most of machine learning in the cloud.
Speaker: Osemeke Isibor, Solutions Architect, AWS
AWS offers a family of intelligent services that provide cloud-native machine learning and deep learning technologies to address your different use cases and needs. For developers looking to add managed AI services to their applications, AWS brings natural language understanding (NLU) and text-to-speech (TTS) with Amazon Polly, visual search and image recognition with Amazon Rekognition, and developer-focused machine learning with Amazon Machine Learning. In this talk you will learn about these services and see demos of their capabilities
An Overview of AI at AWS: Amazon Lex, Amazon Polly, Amazon Rekognition, Apach...Amazon Web Services
by Keith Steward, Solutions Architect, AWS
AI services on the AWS cloud bring deep learning technologies like natural language understanding, automatic speech recognition, computer vision, text-to-speech, and machine learning within reach of every developer. For more in-depth deep learning applications, the Deep Learning AMIs let you create managed, auto-scaling clusters of GPUs for large scale training, or run inference on trained models with compute-optimized or general-purpose CPU instances. Whether you’re just getting started with AI or you’re a deep learning expert, this session will provide a meaningful overview of how to improve scale and efficiency with the AWS Cloud. Level 200
An Overview of AI on the AWS Platform - June 2017 AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- Learn about the breadth of AI services available on the AWS Cloud
- Gain insight into Amazon Lex, Amazon Polly, and Amazon Rekognition
- Learn more about why Apache MXNet is the deep learning framework of choice for AWS
Using AI to Automate and Optimize Media and Entertainment Workloads – Antoine...Amazon Web Services
Find out how companies of all sizes are leveraging AWS services to increase agility, innovation, and to modernize media experiences. Learn how computer vision, object recognition, and conversation engines are changing how media companies engage with consumers.
Similar to AWS_HK_StartupDay_Building Interactive websites while automating for efficiency with Amazon AI Services (20)
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...Amazon Web Services
Il Forecasting è un processo importante per tantissime aziende e viene utilizzato in vari ambiti per cercare di prevedere in modo accurato la crescita e distribuzione di un prodotto, l’utilizzo delle risorse necessarie nelle linee produttive, presentazioni finanziarie e tanto altro. Amazon utilizza delle tecniche avanzate di forecasting, in parte questi servizi sono stati messi a disposizione di tutti i clienti AWS.
In questa sessione illustreremo come pre-processare i dati che contengono una componente temporale e successivamente utilizzare un algoritmo che a partire dal tipo di dato analizzato produce un forecasting accurato.
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...Amazon Web Services
La varietà e la quantità di dati che si crea ogni giorno accelera sempre più velocemente e rappresenta una opportunità irripetibile per innovare e creare nuove startup.
Tuttavia gestire grandi quantità di dati può apparire complesso: creare cluster Big Data su larga scala sembra essere un investimento accessibile solo ad aziende consolidate. Ma l’elasticità del Cloud e, in particolare, i servizi Serverless ci permettono di rompere questi limiti.
Vediamo quindi come è possibile sviluppare applicazioni Big Data rapidamente, senza preoccuparci dell’infrastruttura, ma dedicando tutte le risorse allo sviluppo delle nostre le nostre idee per creare prodotti innovativi.
Ora puoi utilizzare Amazon Elastic Kubernetes Service (EKS) per eseguire pod Kubernetes su AWS Fargate, il motore di elaborazione serverless creato per container su AWS. Questo rende più semplice che mai costruire ed eseguire le tue applicazioni Kubernetes nel cloud AWS.In questa sessione presenteremo le caratteristiche principali del servizio e come distribuire la tua applicazione in pochi passaggi
Vent'anni fa Amazon ha attraversato una trasformazione radicale con l'obiettivo di aumentare il ritmo dell'innovazione. In questo periodo abbiamo imparato come cambiare il nostro approccio allo sviluppo delle applicazioni ci ha permesso di aumentare notevolmente l'agilità, la velocità di rilascio e, in definitiva, ci ha consentito di creare applicazioni più affidabili e scalabili. In questa sessione illustreremo come definiamo le applicazioni moderne e come la creazione di app moderne influisce non solo sull'architettura dell'applicazione, ma sulla struttura organizzativa, sulle pipeline di rilascio dello sviluppo e persino sul modello operativo. Descriveremo anche approcci comuni alla modernizzazione, compreso l'approccio utilizzato dalla stessa Amazon.com.
Come spendere fino al 90% in meno con i container e le istanze spot Amazon Web Services
L’utilizzo dei container è in continua crescita.
Se correttamente disegnate, le applicazioni basate su Container sono molto spesso stateless e flessibili.
I servizi AWS ECS, EKS e Kubernetes su EC2 possono sfruttare le istanze Spot, portando ad un risparmio medio del 70% rispetto alle istanze On Demand. In questa sessione scopriremo insieme quali sono le caratteristiche delle istanze Spot e come possono essere utilizzate facilmente su AWS. Impareremo inoltre come Spreaker sfrutta le istanze spot per eseguire applicazioni di diverso tipo, in produzione, ad una frazione del costo on-demand!
In recent months, many customers have been asking us the question – how to monetise Open APIs, simplify Fintech integrations and accelerate adoption of various Open Banking business models. Therefore, AWS and FinConecta would like to invite you to Open Finance marketplace presentation on October 20th.
Event Agenda :
Open banking so far (short recap)
• PSD2, OB UK, OB Australia, OB LATAM, OB Israel
Intro to Open Finance marketplace
• Scope
• Features
• Tech overview and Demo
The role of the Cloud
The Future of APIs
• Complying with regulation
• Monetizing data / APIs
• Business models
• Time to market
One platform for all: a Strategic approach
Q&A
OpsWorks Configuration Management: automatizza la gestione e i deployment del...Amazon Web Services
Con l'approccio tradizionale al mondo IT per molti anni è stato difficile implementare tecniche di DevOps, che finora spesso hanno previsto attività manuali portando di tanto in tanto a dei downtime degli applicativi interrompendo l'operatività dell'utente. Con l'avvento del cloud, le tecniche di DevOps sono ormai a portata di tutti a basso costo per qualsiasi genere di workload, garantendo maggiore affidabilità del sistema e risultando in dei significativi miglioramenti della business continuity.
AWS mette a disposizione AWS OpsWork come strumento di Configuration Management che mira ad automatizzare e semplificare la gestione e i deployment delle istanze EC2 per mezzo di workload Chef e Puppet.
Scopri come sfruttare AWS OpsWork a garanzia e affidabilità del tuo applicativo installato su Instanze EC2.
Microsoft Active Directory su AWS per supportare i tuoi Windows WorkloadsAmazon Web Services
Vuoi conoscere le opzioni per eseguire Microsoft Active Directory su AWS? Quando si spostano carichi di lavoro Microsoft in AWS, è importante considerare come distribuire Microsoft Active Directory per supportare la gestione, l'autenticazione e l'autorizzazione dei criteri di gruppo. In questa sessione, discuteremo le opzioni per la distribuzione di Microsoft Active Directory su AWS, incluso AWS Directory Service per Microsoft Active Directory e la distribuzione di Active Directory su Windows su Amazon Elastic Compute Cloud (Amazon EC2). Trattiamo argomenti quali l'integrazione del tuo ambiente Microsoft Active Directory locale nel cloud e l'utilizzo di applicazioni SaaS, come Office 365, con AWS Single Sign-On.
Amazon Web Services e VMware organizzano un evento virtuale gratuito il prossimo mercoledì 14 Ottobre dalle 12:00 alle 13:00 dedicato a VMware Cloud ™ on AWS, il servizio on demand che consente di eseguire applicazioni in ambienti cloud basati su VMware vSphere® e di accedere ad una vasta gamma di servizi AWS, sfruttando a pieno le potenzialità del cloud AWS e tutelando gli investimenti VMware esistenti.
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
Crea la tua prima serverless ledger-based app con QLDB e NodeJSAmazon Web Services
Molte aziende oggi, costruiscono applicazioni con funzionalità di tipo ledger ad esempio per verificare lo storico di accrediti o addebiti nelle transazioni bancarie o ancora per tenere traccia del flusso supply chain dei propri prodotti.
Alla base di queste soluzioni ci sono i database ledger che permettono di avere un log delle transazioni trasparente, immutabile e crittograficamente verificabile, ma sono strumenti complessi e onerosi da gestire.
Amazon QLDB elimina la necessità di costruire sistemi personalizzati e complessi fornendo un database ledger serverless completamente gestito.
In questa sessione scopriremo come realizzare un'applicazione serverless completa che utilizzi le funzionalità di QLDB.
Con l’ascesa delle architetture di microservizi e delle ricche applicazioni mobili e Web, le API sono più importanti che mai per offrire agli utenti finali una user experience eccezionale. In questa sessione impareremo come affrontare le moderne sfide di progettazione delle API con GraphQL, un linguaggio di query API open source utilizzato da Facebook, Amazon e altro e come utilizzare AWS AppSync, un servizio GraphQL serverless gestito su AWS. Approfondiremo diversi scenari, comprendendo come AppSync può aiutare a risolvere questi casi d’uso creando API moderne con funzionalità di aggiornamento dati in tempo reale e offline.
Inoltre, impareremo come Sky Italia utilizza AWS AppSync per fornire aggiornamenti sportivi in tempo reale agli utenti del proprio portale web.
Database Oracle e VMware Cloud™ on AWS: i miti da sfatareAmazon Web Services
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
In queste slide, gli esperti AWS e VMware presentano semplici e pratici accorgimenti per facilitare e semplificare la migrazione dei carichi di lavoro Oracle accelerando la trasformazione verso il cloud, approfondiranno l’architettura e dimostreranno come sfruttare a pieno le potenzialità di VMware Cloud ™ on AWS.
Amazon Elastic Container Service (Amazon ECS) è un servizio di gestione dei container altamente scalabile, che semplifica la gestione dei contenitori Docker attraverso un layer di orchestrazione per il controllo del deployment e del relativo lifecycle. In questa sessione presenteremo le principali caratteristiche del servizio, le architetture di riferimento per i differenti carichi di lavoro e i semplici passi necessari per poter velocemente migrare uno o più dei tuo container.
Durante i laboratori pratici, gli esperti AWS ti mostrano quali strumenti aiutano a sviluppare le applicazioni Serverless in locale e nel cloud AWS e ti aiuteranno a programmare i prossimi passi per iniziare ad utilizzare questa tecnologia nella tua azienda.
AWS Serverless per startup: come innovare senza preoccuparsi dei serverAmazon Web Services
La tecnologia Serverless sembra essere perfetta per startup. Il modello di pricing “pay-per-use” e l’infrastruttura che non genera alcun costo in mancanza di traffico rende la struttura di costi estremamente economica ed efficiente per le startup. Inoltre, le architetture Serverless sono pienamente gestite e scalano automaticamente, per questo i team non devono preoccuparsi di improvvise crescite del traffico che, per esempio, possono derivare da campagne marketing di successo. Questi sono solo alcuni dei motivi per cui molte startup hanno deciso di costruire architetture Serverless a supporto del proprio business. Durante il webinar, approfondiremo i servizi Serverless di AWS e come le startup possono utilizzarli per aumentare agilità e innovazione. Approfondiremo il servizio AWS Lambda che permette di eseguire codice per qualunque tipologia di applicazione, senza alcun lavoro di “amministrazione”. Durante la sessione, condivideremo inoltre casi d’uso di startup che hanno implementato con successo la tecnologia Serverless.
Amazon QuickSight è un servizio di business intelligence veloce e innovativo che consente di fornire informazioni dettagliate a tutti gli utenti dell'organizzazione. Come servizio completamente gestito, QuickSight consente di creare e pubblicare facilmente dashboard interattive che includono funzionalità uniche quali ML Insights, Ml Powered Forecasts and Anomaly Detection. Le dashboard sono quindi accessibili da qualsiasi dispositivo e possono essere integrate in applicazioni, portali e siti Web. Nell'ultimo anno QuickSight ha rilasciato oltre 200 nuove funzionalità. In questo webinar forniamo una panoramica dettagliata di QuickSight e una demo live per apprezzarne appieno il potenziale.
3. Our approach for machine learning
Customer-focused
90%+ of our ML roadmap is
defined by customers
Multi-framework
Support for the most
popular frameworks
Pace of innovation
200+ new ML launches and major feature
updates in the
last year
Breadth and depth
A wide range of AI and ML services in-
production
Security and analytics
Deep set of security and
encryption features, with robust analytics
capabilities
Embedded R&D
Customer-centric approach to
advancing the state of the art
4. The AWS ML Stack
Broadest and most complete set of Machine Learning capabilities
VISION SPEECH TEXT SEARCH CHATBOTS PERSONALIZATION FORECASTING FRAUD DEVELOPMENT CONTACT CENTERS
Ground
Truth
AWS
Marketplace
for ML
Neo Augmented
AIBuilt-in
algorithms
Notebooks Experiments Processing
Model
training &
tuning
Debugger Autopilot
Model
hosting
Model Monitor
Deep Learning
AMIs & Containers
GPUs &
CPUs
Elastic
Inference
Inferentia FPGA
Amazon
Rekognition
Amazon
Polly
Amazon
Transcribe
+Medical
Amazon
Comprehend
+Medical
Amazon
Translate
Amazon
Lex
Amazon
Personalize
Amazon
Forecast
Amazon
Fraud Detector
Amazon
CodeGuru
AI SERVICES
ML SERVICES
ML FRAMEWORKS & INFRASTRUCTURE
Amazon
Textract
Amazon
Kendra
Contact Lens
For Amazon Connect
SageMaker Studio IDE
Amazon SageMaker
DeepGraphLibrary
RL Coach
5. Fully managed data
processing jobs and
data labeling
workflows
One-click collaborative
notebooks and built-in,
high performance
algorithms and models
One-click
training Debugging and optimization
One-click
deployment and
autoscaling
Amazon SageMaker helps you build, train, and deploy models
Visually track and
compare experiments
Automatically
spot
concept drift
Fully
managed with
auto-scaling
for 75% less
Prepare Build Train & Tune Deploy & Manage
101011010
010101010
000011110
Collect and
prepare
training data
Choose or bring
your own
ML algorithm
Set up and manage
environments
for training
Train, debug, and
tune models
Deploy
model in
production
Manage training runs Monitor
models
Validate
predictions
Scale and manage
the production
environment
Add human
review of
predictions
Web-based IDE for machine learning
Automatically build and train models
7. AI Services
Pre-trained AI services that require
no ML skills or training
Easily add intelligence to your
existing apps and workflows
Quality and accuracy from
continuously-learning APIs
VISION SPEECH TEXT SEARCH CHATBOTS PERSONALIZATION FORECASTING FRAUD DEVELOPMENT CONTACT CENTERS
Amazon
Rekognition
Amazon
Polly
Amazon
Transcribe
+Medical
Amazon
Comprehend
+Medical
Amazon
Translate
Amazon
Lex
Amazon
Personalize
Amazon
Forecast
Amazon
Fraud Detector
Amazon
CodeGuru
Amazon
Textract
Amazon
Kendra
Contact Lens
For Amazon Connect
14. Policing user-generated content
Age range – 26–43 years
Wearing glasses – 99.9%
Eyes closed – 94%
Mouth open – 96%
Eyes closed – 94%
Barrack Obama – 100%
Not smiling – 60.3%
Female – 100%
15. Challenges of non-AI approach
• Manual process for checking images – Labor intensive
• Non-uniformity – Results vary from resource to resource
• Scalability – Difficult to keep up with the rate of image
generation
16. Example: user-generated content moderation
2. Submit picture
4. DetectFaces
8. SearchFaces
- Blacklist
- Whitelist
- Duplicate check
- Persons of interest
1. Live pic
3. Store live pic
Amazon
Rekognition
Lambda Step functions
5. Recognize Celebrities
Amazon
Rekognition
7. Detect Moderation
Labels
9. Store metadata and
analysis Amazon DynamoDB
Elasticsearch
Blacklist images
Amazon
Rekognition
Amazon
Rekognition
20. Example: automated document processing
2. Extract form
data
1. Capture
document image
Amazon
Textract
Application
Backend
3. Send data to
backend 4. User
submitted data
loaded into
database
Amazon
DynamoDB
23. Amazon Lex – Features
Text and speech language understanding: powered by
the same technology as Amazon Alexa
Deployment to chat services
(Web/Mobile Apps, Facebook, Kik, Slack, Twilio SMS)
Designed for builders: efficient and intuitive tools to
build conversations; scales automatically
Versioning and alias support@
24. Amazon Lex Bots – key concepts
Utterances
Spoken or typed phrases that invoke
your intent
BookHotel
Intents
An intent performs an action in response
to natural language user input
Slots
Slots are input data required to fulfill
the intent
Fulfillment
Fulfillment mechanism for your intent
25. “Book a hotel”
Book hotel
NYC
“Book a hotel in
NYC”
Automatic speech recognition
Hotel booking
New York City
Natural language
understanding
Intent/slot
Model
UtterancesHotel Booking
City New York City
Check in Nov 30th
Check out Dec 2nd
“Your hotel is booked for Nov
30th”
Amazon Polly
Confirmation: “Your hotel is
booked for Nov 30th”
“Can I go ahead
with the booking?
a
in
26. Utterances
I’d like to book a hotel
Can you help me book my hotel?
I want to book a hotel in New York City
I want to make my hotel reservations
27. Slots
Destination City New York City, Seattle, London …
Slot Type Values
Check in Date Valid dates
Check out Date Valid dates
28. Slot elicitation
I’d like to book a hotel
What date do you check in?
New York City
Sure, what city do you want to book?
Nov 30th Check in
11/30/2017
City
New York City
29. Amazon Connect
Self-service, cloud-based contact center service
Real time and
historical analytics
High-quality
voice capability
Call
recording
Skills-based routing
[Automatic Call Distribution (ACD)]
30. Intelligent call center chatbot
Amazon
Connect
Customer
Amazon Lex Lambda:
Fulfillment
DynamoDB:
Customer Data
SNS:
SMS Messaging
Customer calls
Connect to
reschedule an
appointment
Connect calls
Lex chatbot
Lex chatbot calls
Lambda function
to get customer
preferences and
fulfil Intents
Lambda function
sends text message
confirmation via SNS
Customer receives
appointment
confirmation text
message
Lambda
function writes
updates to
DynamoDB
35. Amazon Comprehend – Natural Language Processing
Amazon.com, Inc. is located in Seattle, WA
and was founded July 5, 1994 by Jeff
Bezos. Our customers love buying
everything from books to blenders at
great prices
Named Entities
• Amazon.com: Organization
• Seattle, WA : Location
• July 5th,1994: Date
• Jeff Bezos : Person
Keyphrases
• Our customers
• books
• blenders
• great prices
Sentiment
• Positive
Language
• English
36. Amazon Comprehend – Syntax API
Our customers love buying everything
from books to blenders at great prices
Token
(word)
Part of
Speech
customers Noun
love Verb
books Noun
great Adjective
prices Noun
37. Supported parts of speech
ADJ – Adjective
ADP – Adposition
ADV – Adverb
AUX – Auxiliary
CCONJ – Coordinating Conjunction
DET – Determiner
INTJ - Interjection
NOUN - Noun
NUM – Numeral
O – Other
PART – Particle
PRON – Pronoun
PROPN – Proper Noun
PUNCT – Punctuation
SCONJ – Subordinating
Conjunction
SYM – Symbol
VERB – Verb
40. Popular text analytics use cases
Content Personalization
• Understand related documents based on entities, phrases or even topic similarities for trends
analysis, to drive content personalization and recommendations
Semantic Search
• Index entities for boosting and ranking search results
Intelligent data warehouse
• Query unstructured data in relational databases, processing data within the data lake (Amazon S3)
and then inserting it back into the data warehouse
Social Analytics
• Ingest, process and analyze trends from entities and sentiment from social media posts across
Twitter and Facebook
41. Support for large data sets and topic modeling
STORM
WORLD SERIES
STOCK MARKET
WASHINGTON
LIBRARY OF
NEWS ARTICLES *
Amazon
Comprehend