Machine Learning Workshops at the San Francisco Loft
Automate for Efficiency with Amazon Transcribe and Amazon Translate
Teaching a computer how to understand human language is one of the most challenging problems in computer science. However, significant progress has been made in automatic speech recognition (ASR) and machine translation (MT) to create highly accurate and fluent transcriptions and translations. Amazon Transcribe is an ASR service that makes it easy for developers to add speech to text capability to their applications, and Amazon Translate is a MT service that delivers fast, high-quality, and affordable language translation. In this session, you’ll learn how to weave machine translation and transcription into your workflows, to increase the efficiency and reach of your operations.
Level: 200-300
Speaker: Martin Schade - R&D Engineer, AWS Solutions Architecture
Add Intelligence to Applications with AWS ML: Machine Learning Workshops SFAmazon Web Services
Machine Learning Workshops at the San Francisco Loft
Add Intelligence to Applications with AWS ML Services
Organizations are increasingly turning to machine learning to build intelligent applications and get more insights out of their data in real-time. In this session, you’ll learn about AWS Machine Learning APIs for computer vision and language, and how to get started with these pre-trained services: Amazon Rekognition, Amazon Comprehend, Amazon Transcribe, Amazon Translate, Amazon Polly, and Amazon Lex. We’ll also show how these services connect to AWS’s comprehensive data platform and services to drive the success of your machine learning projects.
Level: 200
Speaker: Liam Morrison - Principal Solutions Architect, AWS
Workshop Build an Image-Based Automatic Alert System with Amazon Rekognition:...Amazon Web Services
Machine Learning Workshops at the San Francisco Loft
Build an Image-Based Automatic Alert System with Amazon Rekognition
This hands-on workshop will walk through how to build a solution that listens and captures images from Twitter, and then compares those images against a reference image to automatically notify you about a new post featuring your favorite celebrity. Additionally, we will integrate sentiment analysis into this image-based automatic alert system in order to gauge whether the determined celebrities are happy, sad, etc. in the posted image.
Level: 200-300
Speakers:
Wayne Davis - Solutions Architect, AWS
Tristan Li - Solutions Architect, AWS
Build Text Analytics Solutions with AWS ML Services: Machine Learning Worksho...Amazon Web Services
Machine Learning Workshops at the San Francisco Loft
Build Text Analytics Solutions with Amazon Comprehend and Amazon Translate
Natural language holds a wealth of information like user sentiment and conversational intent. In this session, we'll demonstrate the capabilities of Amazon Comprehend, a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. We'll show you how to build a VOC (Voice of the Customer) application and integrate it with other AWS services including AWS Lambda, Amazon S3, Amazon Athena, Amazon QuickSight, and Amazon Translate. We’ll also show you additional methods for NLP available through Amazon Sagemaker.
Level: 200-300
Speaker: Ben Snively - Principal Solutions Architect, Data & Analytics, AWS
Using Amazon ML Services for Video Transcription & Translation: Machine Learn...Amazon Web Services
Machine Learning Workshops at the San Francisco Loft
Using Amazon ML Services for Video Transcription and Translation
In this hands-on workshop, participants will use AWS ML services to generate transcripts from audio files, use NLP to analyze those transcripts, and produce subtitles in multiple languages. Using ML, you can keep pace with the proliferation of audio/video content across businesses. Asset managers can unlock hidden value in existing media libraries by finding precise moments when particular keywords or phrases are spoken; video publishers can benefit from subtitle and localized files for reaching global audiences; and IT organizations can utilize transcription data to improve organizational governance.
Level: 200-300
Automate for Efficiency with Amazon Transcribe & Amazon TranslateAmazon Web Services
by Pratap Ramamurthy, Partner Solutions Architect, AWS
Teaching a computer how to understand human language is one of the most challenging problems in computer science. However, significant progress has been made in automatic speech recognition (ASR) and machine translation (MT) to create highly accurate and fluent transcriptions and translations. Amazon Transcribe is an ASR service that makes it easy for developers to add speech to text capability to their applications, and Amazon Translate is a MT service that delivers fast, high-quality, and affordable language translation. In this session, you’ll learn how to weave machine translation and transcription into your workflows, to increase the efficiency and reach of your operations.
Add Intelligence to Applications with AWS ML Services
Organizations are increasingly turning to machine learning to build intelligent applications and get more insights out of their data in real-time. In this session, you’ll learn about AWS Machine Learning APIs for computer vision and language, and how to get started with these pre-trained services: Amazon Rekognition, Amazon Comprehend, Amazon Transcribe, Amazon Translate, Amazon Polly, and Amazon Lex. We’ll also show how these services connect to AWS’s comprehensive data platform and services to drive the success of your machine learning projects.
Level: 200
Speaker: Yash Pant - Enterprise Solutions Architect, AWS
Add Intelligence to Applications with AWS ML Services: Machine Learning Week ...Amazon Web Services
Machine Learning Week at the San Francisco Loft: Add Intelligence to Applications with AWS ML Services
Organizations are increasingly turning to machine learning to build intelligent applications and get more insights out of their data in real-time. In this session, you’ll learn about AWS Machine Learning APIs for computer vision and language, and how to get started with these pre-trained services: Amazon Rekognition, Amazon Comprehend, Amazon Transcribe, Amazon Translate, Amazon Polly, and Amazon Lex. We’ll also show how these services connect to AWS’s comprehensive data platform and services to drive the success of your machine learning projects.
Level: 200
Speaker: Anjana Kandalam - Solutions Architect, AWS
AWS Machine Learning Week SF: Build Intelligent Applications with AWS ML Serv...Amazon Web Services
AWS Machine Learning Week at the San Francisco Loft
Add Intelligence to Applications with AWS ML Services: Organizations are increasingly turning to machine learning to build intelligent applications and get more insights out of their data in real-time. In this session, you’ll learn about AWS Machine Learning APIs for computer vision and language, and how to get started with these pre-trained services: Amazon Rekognition, Amazon Comprehend, Amazon Transcribe, Amazon Translate, Amazon Polly, and Amazon Lex. We’ll also show how these services connect to AWS’s comprehensive data platform and services to drive the success of your machine learning projects.
Speaker: Randall Hunt - Technical Evangelist, AWS
Add Intelligence to Applications with AWS ML: Machine Learning Workshops SFAmazon Web Services
Machine Learning Workshops at the San Francisco Loft
Add Intelligence to Applications with AWS ML Services
Organizations are increasingly turning to machine learning to build intelligent applications and get more insights out of their data in real-time. In this session, you’ll learn about AWS Machine Learning APIs for computer vision and language, and how to get started with these pre-trained services: Amazon Rekognition, Amazon Comprehend, Amazon Transcribe, Amazon Translate, Amazon Polly, and Amazon Lex. We’ll also show how these services connect to AWS’s comprehensive data platform and services to drive the success of your machine learning projects.
Level: 200
Speaker: Liam Morrison - Principal Solutions Architect, AWS
Workshop Build an Image-Based Automatic Alert System with Amazon Rekognition:...Amazon Web Services
Machine Learning Workshops at the San Francisco Loft
Build an Image-Based Automatic Alert System with Amazon Rekognition
This hands-on workshop will walk through how to build a solution that listens and captures images from Twitter, and then compares those images against a reference image to automatically notify you about a new post featuring your favorite celebrity. Additionally, we will integrate sentiment analysis into this image-based automatic alert system in order to gauge whether the determined celebrities are happy, sad, etc. in the posted image.
Level: 200-300
Speakers:
Wayne Davis - Solutions Architect, AWS
Tristan Li - Solutions Architect, AWS
Build Text Analytics Solutions with AWS ML Services: Machine Learning Worksho...Amazon Web Services
Machine Learning Workshops at the San Francisco Loft
Build Text Analytics Solutions with Amazon Comprehend and Amazon Translate
Natural language holds a wealth of information like user sentiment and conversational intent. In this session, we'll demonstrate the capabilities of Amazon Comprehend, a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. We'll show you how to build a VOC (Voice of the Customer) application and integrate it with other AWS services including AWS Lambda, Amazon S3, Amazon Athena, Amazon QuickSight, and Amazon Translate. We’ll also show you additional methods for NLP available through Amazon Sagemaker.
Level: 200-300
Speaker: Ben Snively - Principal Solutions Architect, Data & Analytics, AWS
Using Amazon ML Services for Video Transcription & Translation: Machine Learn...Amazon Web Services
Machine Learning Workshops at the San Francisco Loft
Using Amazon ML Services for Video Transcription and Translation
In this hands-on workshop, participants will use AWS ML services to generate transcripts from audio files, use NLP to analyze those transcripts, and produce subtitles in multiple languages. Using ML, you can keep pace with the proliferation of audio/video content across businesses. Asset managers can unlock hidden value in existing media libraries by finding precise moments when particular keywords or phrases are spoken; video publishers can benefit from subtitle and localized files for reaching global audiences; and IT organizations can utilize transcription data to improve organizational governance.
Level: 200-300
Automate for Efficiency with Amazon Transcribe & Amazon TranslateAmazon Web Services
by Pratap Ramamurthy, Partner Solutions Architect, AWS
Teaching a computer how to understand human language is one of the most challenging problems in computer science. However, significant progress has been made in automatic speech recognition (ASR) and machine translation (MT) to create highly accurate and fluent transcriptions and translations. Amazon Transcribe is an ASR service that makes it easy for developers to add speech to text capability to their applications, and Amazon Translate is a MT service that delivers fast, high-quality, and affordable language translation. In this session, you’ll learn how to weave machine translation and transcription into your workflows, to increase the efficiency and reach of your operations.
Add Intelligence to Applications with AWS ML Services
Organizations are increasingly turning to machine learning to build intelligent applications and get more insights out of their data in real-time. In this session, you’ll learn about AWS Machine Learning APIs for computer vision and language, and how to get started with these pre-trained services: Amazon Rekognition, Amazon Comprehend, Amazon Transcribe, Amazon Translate, Amazon Polly, and Amazon Lex. We’ll also show how these services connect to AWS’s comprehensive data platform and services to drive the success of your machine learning projects.
Level: 200
Speaker: Yash Pant - Enterprise Solutions Architect, AWS
Add Intelligence to Applications with AWS ML Services: Machine Learning Week ...Amazon Web Services
Machine Learning Week at the San Francisco Loft: Add Intelligence to Applications with AWS ML Services
Organizations are increasingly turning to machine learning to build intelligent applications and get more insights out of their data in real-time. In this session, you’ll learn about AWS Machine Learning APIs for computer vision and language, and how to get started with these pre-trained services: Amazon Rekognition, Amazon Comprehend, Amazon Transcribe, Amazon Translate, Amazon Polly, and Amazon Lex. We’ll also show how these services connect to AWS’s comprehensive data platform and services to drive the success of your machine learning projects.
Level: 200
Speaker: Anjana Kandalam - Solutions Architect, AWS
AWS Machine Learning Week SF: Build Intelligent Applications with AWS ML Serv...Amazon Web Services
AWS Machine Learning Week at the San Francisco Loft
Add Intelligence to Applications with AWS ML Services: Organizations are increasingly turning to machine learning to build intelligent applications and get more insights out of their data in real-time. In this session, you’ll learn about AWS Machine Learning APIs for computer vision and language, and how to get started with these pre-trained services: Amazon Rekognition, Amazon Comprehend, Amazon Transcribe, Amazon Translate, Amazon Polly, and Amazon Lex. We’ll also show how these services connect to AWS’s comprehensive data platform and services to drive the success of your machine learning projects.
Speaker: Randall Hunt - Technical Evangelist, AWS
Workshop: Using Amazon ML Services for Video Transcription and Translation Wo...Amazon Web Services
by Pratap Ramamurthy, Partner Solutions Architect, AWS
In this hands-on workshop, participants will use AWS ML services to generate transcripts from audio files, use NLP to analyze those transcripts, and produce subtitles in multiple languages. Using ML, you can keep pace with the proliferation of audio/video content across businesses. Asset managers can unlock hidden value in existing media libraries by finding precise moments when particular keywords or phrases are spoken; video publishers can benefit from subtitle and localized files for reaching global audiences; and IT organizations can utilize transcription data to improve organizational governance.
Build Intelligent Apps with Amazon ML - Language Services - BDA302 - Chicago ...Amazon Web Services
Amazon brings natural language processing, automatic speech recognition, text-to-speech, and neural machine translation technologies within reach of every developer. In this session, learn how you can easily add intelligence to any application with solution-oriented machine learning (ML) services that provide speech, language, and chatbot functionalities. We also share real-world examples of ML in action. See how others are defining and building the next generation of apps that can hear, speak, understand, and interact with the world around us.
Automate for Efficiency with Amazon Transcribe & Amazon Translate: Machine Le...Amazon Web Services
Machine Learning Week at the San Francisco Loft: Automate for Efficiency with Amazon Transcribe & Amazon Translate
Teaching a computer how to understand human language is one of the most challenging problems in computer science. However, significant progress has been made in automatic speech recognition (ASR) and machine translation (MT) to create highly accurate and fluent transcriptions and translations. Amazon Transcribe is an ASR service that makes it easy for developers to add speech to text capability to their applications, and Amazon Translate is a MT service that delivers fast, high-quality, and affordable language translation. In this session, you’ll learn how to weave machine translation and transcription into your workflows, to increase the efficiency and reach of your operations.
Level: 200-300
Speaker: Niranjan Hira - Solutions Architect, Lex
Mike Gillespie - Build Intelligent Applications with AWS ML Services (200).pdfAmazon Web Services
Organizations are increasingly turning to machine learning to build intelligent applications and get more insights out of their data in real-time. In this session, you’ll learn about AWS Machine Learning APIs for computer vision and language, and how to get started with these pre-trained services: Amazon Rekognition, Amazon Comprehend, Amazon Transcribe, Amazon Translate, Amazon Polly, and Amazon Lex. We’ll also show how these services connect to AWS’s comprehensive data platform and services to drive the success of your machine learning projects.
Mike Gillespie - Automate for Efficiency with Amazon Transcribe & Amazon Tran...Amazon Web Services
Teaching a computer how to understand human language is one of the most challenging problems in computer science. However, significant progress has been made in automatic speech recognition (ASR) and machine translation (MT) to create highly accurate and fluent transcriptions and translations. Amazon Transcribe is an ASR service that makes it easy for developers to add speech to text capability to their applications, and Amazon Translate is a MT service that delivers fast, high-quality, and affordable language translation. In this session, you’ll learn how to weave machine translation and transcription into your workflows, to increase the efficiency and reach of your operations.
AWS Machine Learning Week SF: Automate for Efficiency with Amazon Transcribe ...Amazon Web Services
AWS Machine Learning Week at the San Francisco Loft: Automate for Efficiency with Amazon Transcribe & Amazon Translate
Teaching a computer how to understand human language is one of the most challenging problems in computer science. However, significant progress has been made in automatic speech recognition (ASR) and machine translation (MT) to create highly accurate and fluent transcriptions and translations. Amazon Transcribe is an ASR service that makes it easy for developers to add speech to text capability to their applications, and Amazon Translate is a MT service that delivers fast, high-quality, and affordable language translation. In this session, you’ll learn how to weave machine translation and transcription into your workflows, to increase the efficiency and reach of your operations.
Speaker: Martin Schade - R&D Engineer, AWS
NEW LAUNCH! Introducing Amazon Translate – Now in Preview - MCL209 - re:Inven...Amazon Web Services
Amazon Translate is a neural machine translation service that delivers fast, high-quality, and affordable language translation. Neural machine translation uses deep learning to deliver more accurate and more natural sounding translation than older statistical and rule-based translation algorithms. Amazon Translate enables translation at scale so that you can easily translate large volumes of text efficiently to handle tasks like localizing content for international users and facilitating real-time cross-lingual communication.
Join this session to learn more and find out how you get can started with Amazon Translate, today!
Amazon Polly Tips and Tricks: How to Bring Your Text-to-Speech Voices to Life...Amazon Web Services
Although there are many ways to optimize the speech generated by Amazon Polly's text-to-speech voices, you might find it challenging to apply the most effective enhancements in each situation. Learn how you can control pronunciation, intonation, and timing for text-to-speech voices. In this session, you get a comprehensive overview of the available tools and methods available for modifying Amazon Polly speech output, including SSML tags, lexicons, and punctuation. You also get recommendations for streamlining application of these techniques. Come away with insider tips on the best speech optimization techniques to provide a more natural voice experience.
NEW LAUNCH! Feature updates for Amazon Rekognition - MCL336 - re:Invent 2017Amazon Web Services
In this session. We will provide an overview of the latest Amazon Rekognition features including real-time face recognition, Text in Image recognition, and improved face detection.
Amazon Rekognition recently added three new features: detection and recognition of text in images; real-time face recognition across tens of millions of faces; and detection of up to 100 faces in challenging crowded photos. In this session, we will cover features, benefits and use cases for these latest Rekognition features, while highlighting customer examples and a brief demo showcasing Amazon Rekognition.
Build Text Analytics Solutions with Amazon Comprehend and Amazon TranslateAmazon Web Services
by Pratap Ramamurthy, Partner Solutions Architect, AWS
Natural language holds a wealth of information like user sentiment and conversational intent. In this session, we'll demonstrate the capabilities of Amazon Comprehend, a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. We'll show you how to build a VOC (Voice of the Customer) application and integrate it with other AWS services including AWS Lambda, Amazon S3, Amazon Athena, Amazon QuickSight, and Amazon Translate. We’ll also show you additional methods for NLP available through Amazon Sagemaker.
re:Invent re:Cap - An overview of Artificial Intelligence and Machine Learnin...Adrian Hornsby
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.
Demystifying Machine Learning On AWS - AWS Summit Sydney 2018Amazon Web Services
Demystifying Machine Learning on AWS
Machine Learning is having a major impact in our society, but how can we simplify the build, train, and deploy process for all developers and data scientists? Understand how cloud-based machine learning frameworks can help turn your data into intelligence. We will introduce the general machine learning process utilising the AWS Deep Learning AMIs and hear from carsales.com.au about how they built the Cyclops, a Super Human Image Recognition Software on AWS. We will then discuss the new capabilities delivered by Amazon SageMaker and how this product will further reduce the undifferentiated heavy lifting; freeing you up to focus on your business and allow your developers to quickly and easily expand into the world of Machine Learning.
Jenny Davies, Solutions Architect, Amazon Web Services and Agustinus Nalwan, AI and Machine Learning Technical Development Manager, Carsales.com.au
Workshop: Build Deep Learning Applications with TensorFlow and SageMakerAmazon Web Services
by Ahmad Khan, Sr. Solutions Architect, AWS
Deep learning continues to push the state of the art in domains such as computer vision, natural language understanding and recommendation engines. In this workshop, you’ll learn how to get started with the TensorFlow deep learning framework using Amazon SageMaker, a platform to easily build, train and deploy models at scale. You’ll learn how to build a model using TensorFlow by setting up a Jupyter notebook to get started with image and object recognition. You’ll also learn how to quickly train and deploy a model through Amazon SageMaker.
Using Machine Learning on AWS for Continuous Sentiment Analysis from Labeling...Amazon Web Services
by Zignal Labs
Today, machine learning solves a range of everyday business challenges. Companies are leveraging machine learning to understand how their brands are perceived in the marketplace across key stakeholder segments. How does the brand resonate with customers and the media? What product feedback and enhancements can be learned?
By harnessing the power of machine learning, Zignal monitors and analyzes – in real-time – brand conversations across social, broadcast, digital and traditional media channels. In this session, learn how Zignal leverages Amazon SageMaker, Amazon Mechanical Turk, AWS Code Pipeline and AWS Lambda to accurately measure the brand health of major enterprises such as NVIDIA and Airbnb. Zignal will dive deep into how Amazon SageMaker and these services work together on machine learning models in a real-time media environment.
Use Amazon Rekognition to Build a Facial Recognition SystemAmazon Web Services
Amazon Rekognition makes it easy to extract meaningful metadata from visual content. In this workshop, you will work in teams to build a simple system to help track missing persons. You’ll develop a solution that leverages Amazon Rekognition and other AWS services to analyze images from various sources (e.g., social media) and provide authorities with timely reports and alerts on new leads for missing individuals. The solution will entail a repeatable and automated process that follows best practices for architecting in the cloud, such as designing for high availability and scalability.
Building Your Smart Applications with Machine Learning on AWS | AWS WebinarAmazon Web Services
Machine Learning (ML) has long been an arcane topic, accessible only to experts. In this webinar, you will learn how to easily add Amazon API-driven ML services to your education software. Image and video analysis, text-to-speech, speech-to-text, translation, natural language processing: all these are just an API call away. Through code-level demos, we'll show you how to quickly start integrating these services into your education offerings, with zero ML expertise required.
Speaker: Julien Simon, Principal Evangelist AI/ML EMEA, Amazon Web Services
Learn more: https://aws.amazon.com/education
View the video recording here: https://youtu.be/Dsj5KgER6ec
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
AWS STARTUP DAY 2018 I Enhancing Your Startup With Amazon Machine LearningAWS Germany
Learn how to easily add Amazon AI services to your own applications. Find out how to access image and video analysis, text to speech, speech to text, translation, natural language processing: all of which are just an API call away. You'll learn about Amazon SageMaker, Amazon Translate, Amazon Polly, Amazon Transcribe, Amazon Comprehend, Amazon Rekognition, we'll show you how to quickly get started with these services, with zero AI expertise required.
Automate for Efficiency with Amazon Transcribe and Amazon TranslateAmazon Web Services
Teaching a computer how to understand human language is one of the most challenging problems in computer science. However, significant progress has been made in automatic speech recognition (ASR) and machine translation (MT) to create highly accurate and fluent transcriptions and translations. Amazon Transcribe is an ASR service that makes it easy for developers to add speech to text capability to their applications, and Amazon Translate is a MT service that delivers fast, high-quality, and affordable language translation. In this session, you’ll learn how to weave machine translation and transcription into your workflows, to increase the efficiency and reach of your operations.
Building Online Communities Without Language Barriers (AIM339) - AWS re:Inven...Amazon Web Services
Most communities are currently language specific. To engage in a community the user must speak the language native language. In this chalk talk, we will discuss how you can integrate state of the art machine translation to enable users to effectively share and consume content in their language of choice and create truly global communities. Broadening the user base through seamless language translation helps developers increase participation and contribution, ultimately improving the economics of their applications.
Teaching a computer how to understand human language is one of the most challenging problems in computer science. However, significant progress has been made in automatic speech recognition (ASR) and machine translation in creating highly accurate and fluent transcriptions and translations. Amazon Transcribe is an ASR service that makes it easy for developers to add speech-to-text capability to their applications, and Amazon Translate is a machine translation service that delivers fast, high-quality, and affordable language translation. In this session, you learn how companies are weaving machine translation and transcription into their workflows to increase the efficiency and reach of their operations.
Workshop: Using Amazon ML Services for Video Transcription and Translation Wo...Amazon Web Services
by Pratap Ramamurthy, Partner Solutions Architect, AWS
In this hands-on workshop, participants will use AWS ML services to generate transcripts from audio files, use NLP to analyze those transcripts, and produce subtitles in multiple languages. Using ML, you can keep pace with the proliferation of audio/video content across businesses. Asset managers can unlock hidden value in existing media libraries by finding precise moments when particular keywords or phrases are spoken; video publishers can benefit from subtitle and localized files for reaching global audiences; and IT organizations can utilize transcription data to improve organizational governance.
Build Intelligent Apps with Amazon ML - Language Services - BDA302 - Chicago ...Amazon Web Services
Amazon brings natural language processing, automatic speech recognition, text-to-speech, and neural machine translation technologies within reach of every developer. In this session, learn how you can easily add intelligence to any application with solution-oriented machine learning (ML) services that provide speech, language, and chatbot functionalities. We also share real-world examples of ML in action. See how others are defining and building the next generation of apps that can hear, speak, understand, and interact with the world around us.
Automate for Efficiency with Amazon Transcribe & Amazon Translate: Machine Le...Amazon Web Services
Machine Learning Week at the San Francisco Loft: Automate for Efficiency with Amazon Transcribe & Amazon Translate
Teaching a computer how to understand human language is one of the most challenging problems in computer science. However, significant progress has been made in automatic speech recognition (ASR) and machine translation (MT) to create highly accurate and fluent transcriptions and translations. Amazon Transcribe is an ASR service that makes it easy for developers to add speech to text capability to their applications, and Amazon Translate is a MT service that delivers fast, high-quality, and affordable language translation. In this session, you’ll learn how to weave machine translation and transcription into your workflows, to increase the efficiency and reach of your operations.
Level: 200-300
Speaker: Niranjan Hira - Solutions Architect, Lex
Mike Gillespie - Build Intelligent Applications with AWS ML Services (200).pdfAmazon Web Services
Organizations are increasingly turning to machine learning to build intelligent applications and get more insights out of their data in real-time. In this session, you’ll learn about AWS Machine Learning APIs for computer vision and language, and how to get started with these pre-trained services: Amazon Rekognition, Amazon Comprehend, Amazon Transcribe, Amazon Translate, Amazon Polly, and Amazon Lex. We’ll also show how these services connect to AWS’s comprehensive data platform and services to drive the success of your machine learning projects.
Mike Gillespie - Automate for Efficiency with Amazon Transcribe & Amazon Tran...Amazon Web Services
Teaching a computer how to understand human language is one of the most challenging problems in computer science. However, significant progress has been made in automatic speech recognition (ASR) and machine translation (MT) to create highly accurate and fluent transcriptions and translations. Amazon Transcribe is an ASR service that makes it easy for developers to add speech to text capability to their applications, and Amazon Translate is a MT service that delivers fast, high-quality, and affordable language translation. In this session, you’ll learn how to weave machine translation and transcription into your workflows, to increase the efficiency and reach of your operations.
AWS Machine Learning Week SF: Automate for Efficiency with Amazon Transcribe ...Amazon Web Services
AWS Machine Learning Week at the San Francisco Loft: Automate for Efficiency with Amazon Transcribe & Amazon Translate
Teaching a computer how to understand human language is one of the most challenging problems in computer science. However, significant progress has been made in automatic speech recognition (ASR) and machine translation (MT) to create highly accurate and fluent transcriptions and translations. Amazon Transcribe is an ASR service that makes it easy for developers to add speech to text capability to their applications, and Amazon Translate is a MT service that delivers fast, high-quality, and affordable language translation. In this session, you’ll learn how to weave machine translation and transcription into your workflows, to increase the efficiency and reach of your operations.
Speaker: Martin Schade - R&D Engineer, AWS
NEW LAUNCH! Introducing Amazon Translate – Now in Preview - MCL209 - re:Inven...Amazon Web Services
Amazon Translate is a neural machine translation service that delivers fast, high-quality, and affordable language translation. Neural machine translation uses deep learning to deliver more accurate and more natural sounding translation than older statistical and rule-based translation algorithms. Amazon Translate enables translation at scale so that you can easily translate large volumes of text efficiently to handle tasks like localizing content for international users and facilitating real-time cross-lingual communication.
Join this session to learn more and find out how you get can started with Amazon Translate, today!
Amazon Polly Tips and Tricks: How to Bring Your Text-to-Speech Voices to Life...Amazon Web Services
Although there are many ways to optimize the speech generated by Amazon Polly's text-to-speech voices, you might find it challenging to apply the most effective enhancements in each situation. Learn how you can control pronunciation, intonation, and timing for text-to-speech voices. In this session, you get a comprehensive overview of the available tools and methods available for modifying Amazon Polly speech output, including SSML tags, lexicons, and punctuation. You also get recommendations for streamlining application of these techniques. Come away with insider tips on the best speech optimization techniques to provide a more natural voice experience.
NEW LAUNCH! Feature updates for Amazon Rekognition - MCL336 - re:Invent 2017Amazon Web Services
In this session. We will provide an overview of the latest Amazon Rekognition features including real-time face recognition, Text in Image recognition, and improved face detection.
Amazon Rekognition recently added three new features: detection and recognition of text in images; real-time face recognition across tens of millions of faces; and detection of up to 100 faces in challenging crowded photos. In this session, we will cover features, benefits and use cases for these latest Rekognition features, while highlighting customer examples and a brief demo showcasing Amazon Rekognition.
Build Text Analytics Solutions with Amazon Comprehend and Amazon TranslateAmazon Web Services
by Pratap Ramamurthy, Partner Solutions Architect, AWS
Natural language holds a wealth of information like user sentiment and conversational intent. In this session, we'll demonstrate the capabilities of Amazon Comprehend, a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. We'll show you how to build a VOC (Voice of the Customer) application and integrate it with other AWS services including AWS Lambda, Amazon S3, Amazon Athena, Amazon QuickSight, and Amazon Translate. We’ll also show you additional methods for NLP available through Amazon Sagemaker.
re:Invent re:Cap - An overview of Artificial Intelligence and Machine Learnin...Adrian Hornsby
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.
Demystifying Machine Learning On AWS - AWS Summit Sydney 2018Amazon Web Services
Demystifying Machine Learning on AWS
Machine Learning is having a major impact in our society, but how can we simplify the build, train, and deploy process for all developers and data scientists? Understand how cloud-based machine learning frameworks can help turn your data into intelligence. We will introduce the general machine learning process utilising the AWS Deep Learning AMIs and hear from carsales.com.au about how they built the Cyclops, a Super Human Image Recognition Software on AWS. We will then discuss the new capabilities delivered by Amazon SageMaker and how this product will further reduce the undifferentiated heavy lifting; freeing you up to focus on your business and allow your developers to quickly and easily expand into the world of Machine Learning.
Jenny Davies, Solutions Architect, Amazon Web Services and Agustinus Nalwan, AI and Machine Learning Technical Development Manager, Carsales.com.au
Workshop: Build Deep Learning Applications with TensorFlow and SageMakerAmazon Web Services
by Ahmad Khan, Sr. Solutions Architect, AWS
Deep learning continues to push the state of the art in domains such as computer vision, natural language understanding and recommendation engines. In this workshop, you’ll learn how to get started with the TensorFlow deep learning framework using Amazon SageMaker, a platform to easily build, train and deploy models at scale. You’ll learn how to build a model using TensorFlow by setting up a Jupyter notebook to get started with image and object recognition. You’ll also learn how to quickly train and deploy a model through Amazon SageMaker.
Using Machine Learning on AWS for Continuous Sentiment Analysis from Labeling...Amazon Web Services
by Zignal Labs
Today, machine learning solves a range of everyday business challenges. Companies are leveraging machine learning to understand how their brands are perceived in the marketplace across key stakeholder segments. How does the brand resonate with customers and the media? What product feedback and enhancements can be learned?
By harnessing the power of machine learning, Zignal monitors and analyzes – in real-time – brand conversations across social, broadcast, digital and traditional media channels. In this session, learn how Zignal leverages Amazon SageMaker, Amazon Mechanical Turk, AWS Code Pipeline and AWS Lambda to accurately measure the brand health of major enterprises such as NVIDIA and Airbnb. Zignal will dive deep into how Amazon SageMaker and these services work together on machine learning models in a real-time media environment.
Use Amazon Rekognition to Build a Facial Recognition SystemAmazon Web Services
Amazon Rekognition makes it easy to extract meaningful metadata from visual content. In this workshop, you will work in teams to build a simple system to help track missing persons. You’ll develop a solution that leverages Amazon Rekognition and other AWS services to analyze images from various sources (e.g., social media) and provide authorities with timely reports and alerts on new leads for missing individuals. The solution will entail a repeatable and automated process that follows best practices for architecting in the cloud, such as designing for high availability and scalability.
Building Your Smart Applications with Machine Learning on AWS | AWS WebinarAmazon Web Services
Machine Learning (ML) has long been an arcane topic, accessible only to experts. In this webinar, you will learn how to easily add Amazon API-driven ML services to your education software. Image and video analysis, text-to-speech, speech-to-text, translation, natural language processing: all these are just an API call away. Through code-level demos, we'll show you how to quickly start integrating these services into your education offerings, with zero ML expertise required.
Speaker: Julien Simon, Principal Evangelist AI/ML EMEA, Amazon Web Services
Learn more: https://aws.amazon.com/education
View the video recording here: https://youtu.be/Dsj5KgER6ec
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
AWS STARTUP DAY 2018 I Enhancing Your Startup With Amazon Machine LearningAWS Germany
Learn how to easily add Amazon AI services to your own applications. Find out how to access image and video analysis, text to speech, speech to text, translation, natural language processing: all of which are just an API call away. You'll learn about Amazon SageMaker, Amazon Translate, Amazon Polly, Amazon Transcribe, Amazon Comprehend, Amazon Rekognition, we'll show you how to quickly get started with these services, with zero AI expertise required.
Automate for Efficiency with Amazon Transcribe and Amazon TranslateAmazon Web Services
Teaching a computer how to understand human language is one of the most challenging problems in computer science. However, significant progress has been made in automatic speech recognition (ASR) and machine translation (MT) to create highly accurate and fluent transcriptions and translations. Amazon Transcribe is an ASR service that makes it easy for developers to add speech to text capability to their applications, and Amazon Translate is a MT service that delivers fast, high-quality, and affordable language translation. In this session, you’ll learn how to weave machine translation and transcription into your workflows, to increase the efficiency and reach of your operations.
Building Online Communities Without Language Barriers (AIM339) - AWS re:Inven...Amazon Web Services
Most communities are currently language specific. To engage in a community the user must speak the language native language. In this chalk talk, we will discuss how you can integrate state of the art machine translation to enable users to effectively share and consume content in their language of choice and create truly global communities. Broadening the user base through seamless language translation helps developers increase participation and contribution, ultimately improving the economics of their applications.
Teaching a computer how to understand human language is one of the most challenging problems in computer science. However, significant progress has been made in automatic speech recognition (ASR) and machine translation in creating highly accurate and fluent transcriptions and translations. Amazon Transcribe is an ASR service that makes it easy for developers to add speech-to-text capability to their applications, and Amazon Translate is a machine translation service that delivers fast, high-quality, and affordable language translation. In this session, you learn how companies are weaving machine translation and transcription into their workflows to increase the efficiency and reach of their operations.
Improve Your Customer Experience with Machine Translation (AIM321) - AWS re:I...Amazon Web Services
Machine Translation powers Amazon’s international expansion. Sign up to learn how you can leverage Amazon Translate to increase customer satisfaction, cut down response times, and build a more efficient customer support operation. For example, you can add real-time translation to chat, email, and helpdesk so an English-speaking agent can communicate with customers in their preferred language, or translate your knowledge base into multiple languages to make it accessible to customers and employees around the world.
Introduction to AWS ML Application Services - BDA202 - Toronto AWS SummitAmazon Web Services
Amazon brings computer vision, natural language processing, speech recognition, text-to-speech, and machine translation within the reach of every developer. API-driven application services enable developers to easily plug in pre-built AI functionality into their applications and automate manual workflows. Join us to learn more about new language capabilities and text-in-image extraction. We also share how others are building the next generation of intelligent apps that can see, hear, speak, understand, and interact with the world around us.
BDA302 Building Intelligent Apps with AWS Machine Learning Language ServicesAmazon Web Services
Amazon brings natural language processing (NLP), automatic speech recognition (ASR), text-to-speech (TTS), and neural machine translation (NMT) technologies within reach of every developer. In this session, learn how you can easily add intelligence to any application with solution-oriented machine learning (ML) services that provide speech, language, and chatbot functionalities. We also share real-world examples of ML in action. See how others are defining and building the next generation of apps that can hear, speak, understand, and interact with the world around us.
Sviluppare applicazioni voice-first con AWS e Amazon AlexaAmazon Web Services
Come possiamo sviluppare applicazioni che siano allo stesso tempo scalabili, manutenibili, cost-effective, intelligenti e voice-first? La suite di servizi AWS basati su Machine Learning e Deep Learning offre ad ogni sviluppatore la possibilità di integrare funzionalità avanzate di riconoscimento vocale, comprensione del linguaggio naturale, rendering audio e traduzione automatica.
In questo webinar, Alex ed Arianna discuteranno le tecniche e le best practice per implementare interfacce vocali tramite i servizi AWS. Arianna, technical evangelist per Amazon Alexa, introdurrà Alexa e mostrerà come sviluppare esperienze vocali per quest’ultima.
Breaking Language Barriers with AI - Web Summit 2018Boaz Ziniman
AI and machine learning allow developers to introduce new language capabilities in their apps and use Natural Language Processing and Natural Language Understanding to break language barriers, add new functionality and expand their target audience. This session will focus on several AWS AI services for developers, that allow you to add such functionality to your code with minimal effort. We'll build an automatic translator, interact with text to speech and try to extract sentiments from live text coming from different feeds.
Breaking Language Barriers with AI: AWS Developer Workshop - Web Summit 2018Amazon Web Services
Breaking Language Barriers with AI: AWS Developer Workshop - Web Summit 2018
AI and Machine learning allow developers to introduce new language capabilities in their apps and use Natural Language Processing and Natural Language Understanding to break language barriers, add new functionality and expand their target audience. This session will focus on several AWS AI services for developers, that allow you to add such functionality to your code with minimal effort. We will build an automatic translator, interact with text to speech and try to extract sentiments from live text coming from different feeds.
Speaker: Boaz Ziniman - Technical Evangelist, AWS
Amazon brings natural language processing, automatic speech recognition, text-to-speech, and neural machine translation technologies within reach of every developer. In this session, learn how you can easily add intelligence to any application with solution-oriented machine learning (ML) services that provide speech, language, and chatbot functionalities. We also share real-world examples of ML in action. See how others are defining and building the next generation of apps that can hear, speak, understand, and interact with the world around us.
Improving Customer Experience: Enhanced Customer Insights Using Natural Langu...Amazon Web Services
In this session, we’ll discuss how to utilize natural language processing (NLP) to analyze data sources, such as user sentiments, conversational intent, and social media. Machine learning solutions help us bring deeper insights and relationships in texts to reduce the analysis time from weeks to days. We will highlight how quickly a machine learning-based solution can be deployed. We will dive deep into AWS services, such as AWS Lambda, Amazon SageMaker, Amazon Comprehend (Classification), Topic Modeling, and Amazon Transcribe, to rapidly develop a natural language search and analysis application to meet such requirements. We will also demonstrate how to ingest social media Tweets to generate a sentiment score to engage with the customer more effectively.
Machine Learning: Beyond the Hype. Presentation slides from Darin Briskman, Chief Technical Evangelist, Amazon Web Services at the Canadian Executive Cloud & DevSecOps Summit. May 4, 2018 in Toronto and May 11, 2018 in Vancouver. Hosted by TriNimbus
For the Enterprise, Artificial Intelligence (AI) materializes into solutions that improve customers' experiences by optimizing, automating, and personalizing high-volume tasks while lowering cost and time to market, therefore accelerating innovation. Augmented Reality (AR) and Virtual Reality (VR) based solutions offer a promising future in the enterprise allowing engagement with data in innovative ways. In this session, we take a look at how AWS is democratizing AI, AR and VR to enable innovation in the enterprise by building applications quickly and easily without requiring specialized programming.
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.
NEW LAUNCH! Introducing Amazon Transcribe – Now in Preview - MCL215 - re:Inve...Amazon Web Services
Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy for developers to add speech to text capability to their applications. The ASR service can be used across a breadth of industries. For example, customer contact centers can convert call recordings into text for further analysis of what drives positive outcomes; media content producers can automate subtitling workflows for greater reach, and marketers and advertisers can enhance content discovery and display more targeted advertising based on the extracted metadata.
Create Smart and Interactive Apps with Intelligent Language Services on AWS (...Amazon Web Services
Amazon brings natural language processing, automatic speech recognition, text-to-speech services, and neural machine translation technologies within the reach of every developers. In this session, learn how to add intelligence to any application with machine learning services that provide language and chatbot functions. See how others are defining and building the next generation of apps that can hear, speak, understand, and interact with the world around us.
Transform the Modern Contact Center Using Machine Learning and Analytics (AIM...Amazon Web Services
Analyzing customer service interactions across channels provides a complete 360-degree view of customers. By capturing all interactions, you can better identify the root cause of issues and improve first-call resolution and customer satisfaction. In this session, learn how to integrate Amazon Connect and AWS machine learning services, such Amazon Lex, Amazon Transcribe, and Amazon Comprehend, to quickly process and analyze thousands of customer conversations and gain valuable insights. With speech and text analytics, you can pick up on emerging service-related trends before they get escalated or identify and address a potential widespread problem at its inception.
AWS Machine Learning Week SF: Using Amazon ML Services for Video Transcriptio...Amazon Web Services
AWS Machine Learning Week at the San Francisco Loft: In this hands-on workshop, participants will use AWS ML services to generate transcripts from audio files, use NLP to analyze those transcripts, and produce subtitles in multiple languages. Using ML, you can keep pace with the proliferation of audio/video content across businesses. Asset managers can unlock hidden value in existing media libraries by finding precise moments when particular keywords or phrases are spoken; video publishers can benefit from subtitle and localized files for reaching global audiences; and IT organizations can utilize transcription data to improve organizational governance.
Speaker: Sireesha Muppala - Solutions Architect, AWS
Powering Multilingual Video Transcription, Translation, and Search (AIM337) -...Amazon Web Services
Automatic video transcription and translation can help make videos more available and accessible to a global audience in many languages, enabling your employees or customers to access, understand, and benefit from your content. In this chalk talk, we discuss how to transcribe videos, translate them in the required languages in a multilingual application, and enable video search in the viewer’s preferred language—all in an automated and cost-effective manner.
Similar to Automate for Efficiency with Amazon Transcribe & Amazon Translate: Machine Learning Workshops SF (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
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.
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.
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.
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.