AWS Machine Learning Blog

Open Influence uses Amazon Rekognition to enhance its influencer marketing platform

Open Influence is an end-to-end influencer marketing platform that uses artificial intelligence to enable global brands and agencies to quickly and easily identify relevant influencers.  Influencer marketing has become a popular way for corporate brand marketers to work with influential leaders on social media to reach a specific audience. These influencers are critical in executing […]

Read More

Creating virtual guided navigation using a Question and Answer Bot with Amazon Lex and Amazon Alexa

If our users are using Question and Answer Bot (QnABot), and they are getting the right answers for their questions, what else can you do for them? Now you can create a bot to guide them through a series of logically connected answers. This means, for example, that the bot can guide them through the […]

Read More

Create a questionnaire bot with Amazon Lex and Amazon Alexa

In the Create a Question and Answer Bot with Amazon Lex and Amazon Alexa blog post, we showed you how you could create a QnABot (pronounced “Q and A Bot”) for a situation in which your users have questions and you have answers. Now, what if this situation were reversed? What if you could ask […]

Read More

Video analytics in the cloud and at the edge with AWS DeepLens and Kinesis Video Streams

Yesterday we announced the integration of AWS DeepLens with Amazon Kinesis Video Streams, allowing you to easily and securely stream a video feed from AWS DeepLens to Amazon Kinesis Video Streams for analytics, machine learning and other processing. To help you understand the solution that integrates AWS DeepLens and Kinesis Video Streams, we’ll recap the […]

Read More

Analyze US census data for population segmentation using Amazon SageMaker

In the United States, with the 2018 midterm elections approaching, people are looking for more information about the voting process. This blog post explores how we can apply machine learning (ML) to better integrate science into the task of understanding the electorate. Typically for machine learning applications, clear use cases are derived from labelled data. […]

Read More

VidMob combines computer vision and language AI services for data-driven creative asset production

VidMob is a social video creation platform that marketers of all sizes can use to develop personalized advertising communications at scale. VidMob uses machine learning (ML) to power its SaaS application. This application uses metadata extraction and sentiment analysis to provide marketers with actionable insights into which creative assets resonate with their intended audience, and […]

Read More

AWS internal use-case: Evaluating and adopting Amazon SageMaker within AWS Marketing

We’re the AWS Marketing Data Science team. We use advanced analytical and machine learning (ML) techniques so we can share insights into business problems across the AWS customer lifecycle, such as ML-driven scoring of sales leads, ML-based targeting segments, and econometric models for downstream impact measurement. Within Amazon, each team operates independently and owns the […]

Read More

Amazon SageMaker console now supports training job cloning

Today we are launching the training job cloning feature on the Amazon SageMaker console, which makes it much easier for you to create training jobs based on existing ones. When you use Amazon SageMaker, it’s common to run multiple training jobs using different training sets and identical configuration. It’s also common to adjust a specific […]

Read More

AWS Deep Learning AMIs now include Horovod for faster multi-GPU TensorFlow training on Amazon EC2 P3 instances

The AWS Deep Learning AMIs for Ubuntu and Amazon Linux now come pre-installed and fully configured with Horovod, the popular open source distributed training framework to scale TensorFlow training on multiple GPUs. This is an update to the optimized build of TensorFlow 1.8 that we launched in early May. This custom build of TensorFlow 1.8 […]

Read More