Favorite 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
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Shared by AWS Machine Learning July 28, 2020
Favorite 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
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Shared by AWS Machine Learning July 28, 2020
Favorite 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
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Shared by AWS Machine Learning July 25, 2020
Favorite 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
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Shared by AWS Machine Learning July 25, 2020
Favorite Organizations across industries have a lot of unstructured data that you can evaluate to get entity-based insights. You may also want to add your own entity types unique to your business, like proprietary part codes or industry-specific terms. To create a natural language processing (NLP)-based model, you need to
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Shared by AWS Machine Learning July 24, 2020
Favorite 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
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Shared by AWS Machine Learning July 23, 2020
Favorite As solutions architects working in Brazil, we often translate technical content from English to other languages. Doing so manually takes a lot of time, especially when dealing with presentations—in contrast to plain text documents, their content is spread across various areas in multiple slides. To solve that, we wrote
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Shared by AWS Machine Learning July 22, 2020
Favorite In this post you will compile an open-source TensorFlow version of OpenPose using AWS Neuron and fine tune its inference performance for AWS Inferentia based instances. You will set up a benchmarking environment, measure the image processing pipeline throughput, and quantify the price-performance improvements as compared to a GPU
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Shared by AWS Machine Learning July 22, 2020
Favorite When you build models with the Apache MXNet deep learning framework, you can take advantage of the expansive model zoo provided by GluonCV to quickly train state-of-the-art computer vision algorithms for image and video processing. A typical development environment for training consists of a Jupyter notebook hosted on a
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Shared by AWS Machine Learning July 22, 2020
Favorite This is a guest post by Mark Wood at Pulselive. In their own words, “Pulselive, based out of the UK, is the proud digital partner to some of the biggest names in sports.” At Pulselive, we create experiences sports fans can’t live without; whether that’s the official Cricket World
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Shared by AWS Machine Learning July 22, 2020