AWS Machine Learning Blog

Category: Artificial Intelligence

Create a multi-region Amazon Lex bot with Amazon Connect for high availability

AWS customers rely on Amazon Lex bots to power their Amazon Connect self service conversational experiences on telephone and other channels. With Amazon Lex, callers (or customers, in Amazon Connect terminology) can get their questions conveniently answered regardless of agent availability. What architecture patterns can you use to make a bot resilient to service availability issues? In this […]

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Optimizing your engagement marketing with personalized recommendations using Amazon Personalize and Braze

Today’s marketer has a wide array of channels to communicate with their customers. However, sending the right message to the right customer on the right channel at the right time remains the preeminent challenge marketers face. In this post, I show you how to combine Braze, a customer engagement platform built on AWS for today’s […]

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Translating documents, spreadsheets, and presentations in Office Open XML format using Amazon Translate

Now you can translate .docx, .xlsx, and .pptx documents using Amazon Translate. Every organization creates documents, spreadsheets, and presentations to communicate and share information with a large group and keep records for posterity. These days, we interact with people who don’t share the same language as ours. The need for translating such documents has become […]

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Simplifying application onboarding with Amazon CodeGuru Profiler

Amazon CodeGuru Profiler provides recommendations to help you continuously fine-tune your application’s performance. It does this by collecting runtime performance data from your live applications. It looks for your most expensive lines of code continuously and provides intelligent recommendations. This helps you more easily understand your applications’ runtime behavior so you can optimize their performance, […]

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How SNCF Réseau and Olexya migrated a Caffe2 vision pipeline to Managed Spot Training in Amazon SageMaker

This blog post is co-written by guest authors from SNCF and Olexya. Transportation and logistics are fertile ground for machine learning (ML). In this post, we show how the French state-owned railway company Société Nationale des Chemins de fer Français (SNCF) uses ML from AWS with the help of its technology partner Olexya to research, […]

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Building a multilingual question and answer bot with Amazon Lex

You can use Amazon Lex to build a question and answer chatbot. However, if you live in a non-English-speaking country or your business has global reach, you will want a multilingual bot to cater to all your users. This post describes how to achieve that by using the multi-language functionality of your question and answer […]

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Enhancing your chatbot experience with web browsing

Chatbots are popping up everywhere. They are qualifying leads, assisting with sales, and automating customer service. However, conversational chatbot experiences have been limited to the space available within the chatbot window. What if these web-based chatbots could provide an interactive experience that expanded beyond the chat window to include relevant web content based on user […]

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Processing PDF documents with a human loop using Amazon Textract and Amazon Augmented AI

Businesses across many industries, including financial, medical, legal, and real estate, process a large number of documents for different business operations. Healthcare and life science organizations, for example, need to access data within medical records and forms to fulfill medical claims and streamline administrative processes. Amazon Textract is a machine learning (ML) service that makes […]

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Setting up human review of your NLP-based entity recognition models with Amazon SageMaker Ground Truth, Amazon Comprehend, and Amazon A2I

Update Aug 12, 2020 – New features: Amazon Comprehend adds five new languages(Spanish, French, German, Italian and Portuguese) read here. Amazon Comprehend increased the limit of number of entities per custom entity model from 12 to 25 read here. Organizations across industries have a lot of unstructured data that you can evaluate to get entity-based […]

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Extracting custom entities from documents with Amazon Textract and Amazon Comprehend

Amazon Textract is a machine learning (ML) service that makes it easy to extract text and data from scanned documents. Textract goes beyond simple optical character recognition (OCR) to identify the contents of fields in forms and information stored in tables. This allows you to use Amazon Textract to instantly “read” virtually any type of […]

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