AWS Machine Learning Blog

Category: Analytics

Building a visual search application with Amazon SageMaker and Amazon ES

Sometimes it’s hard to find the right words to describe what you’re looking for. As the adage goes, “A picture is worth a thousand words.” Often, it’s easier to show a physical example or image than to try to describe an item with words, especially when using a search engine to find what you’re looking […]

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Detecting and visualizing telecom network outages from tweets with Amazon Comprehend

In today’s world, social media has become a place where customers share their experiences with services that they consume. Every telecom provider wants to have the ability to understand their customer pain points as soon as possible and to do this carriers frequently establish a social media team within their NOC (network operation center). This […]

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Visualizing Amazon SageMaker machine learning predictions with Amazon QuickSight

AWS is excited to announce the general availability of Amazon SageMaker integration in QuickSight. You can now integrate your own Amazon SageMaker ML models with QuickSight to analyze the augmented data and use it directly in your business intelligence dashboards. As a business analyst, data engineer, or data scientist, you can perform ML inference in […]

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Build forecasts and find anomalies from your data with Amazon QuickSight ML Insights

As technology is advancing, your business is collecting more and more data from different sources. After collecting so many data points, it is often challenging to find the right insights to help your business grow. Dashboards are great at visualizing your data, based upon how you built them, but not always great at finding hidden […]

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Building a business intelligence dashboard for your Amazon Lex bots

You’ve rolled out a conversational interface powered by Amazon Lex, with a goal of improving the user experience for your customers. Now you want to track how well it’s working. Are your customers finding it helpful? How are they using it? Do they like it enough to come back? How can you analyze their interactions […]

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Building machine learning workflows with AWS Data Exchange and Amazon SageMaker

Thanks to cloud services such as Amazon SageMaker and AWS Data Exchange, machine learning (ML) is now easier than ever. This post explains how to build a model that predicts restaurant grades of NYC restaurants using AWS Data Exchange and Amazon SageMaker. We use a dataset of 23,372 restaurant inspection grades and scores from AWS […]

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Exploring images on social media using Amazon Rekognition and Amazon Athena

If you’re like most companies, you wish to better understand your customers and your brand image. You’d like to track the success of your marketing campaigns, and the topics of interest—or frustration—for your customers. Social media promises to be a rich source of this kind of information, and many companies are beginning to collect, aggregate, […]

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Enable smart text analytics using Amazon Elasticsearch Service and Amazon Comprehend

We’re excited to announce an end-to-end solution that leverages natural language processing to analyze and visualize unstructured text in your Amazon Elasticsearch Service domain with Amazon Comprehend in the AWS Cloud. You can deploy this solution in minutes with an AWS CloudFormation template and visualize your data in a Kibana dashboard. Amazon Elasticsearch Service (Amazon ES) […]

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Exploring data warehouse tables with machine learning and Amazon SageMaker notebooks

Are you a data scientist with data warehouse tables that you’d like to explore in your machine learning (ML) environment? If so, read on. In this post, I show you how to perform exploratory analysis on large datasets stored in your data warehouse and cataloged in your AWS Glue Data Catalog from your Amazon SageMaker […]

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Analyze live video at scale in real time using Amazon Kinesis Video Streams and Amazon SageMaker

We are excited to announce the launch of the Amazon Kinesis Video Streams Inference Template (KIT) for Amazon SageMaker. This capability enables customers to attach Kinesis Video streams to Amazon SageMaker endpoints in minutes. This drives real-time inferences without having to use any other libraries or write custom software to integrate the services. The KIT comprises […]

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