AWS Machine Learning Blog

Starting today, you can easily train and deploy your PyTorch deep learning models in Amazon SageMaker. This is the fourth deep learning framework that Amazon SageMaker has added support for, in addition to TensorFlow, Apache MXNet, and Chainer.  Just like with those frameworks, now you can write your PyTorch script like you normally would and […]

For AWS government customers and organizations in government-regulated industries it is critical to communicate with people in their preferred languages. CSA Research shows that 51 percent of consumers prefer content in their own language, even if the language quality is less than perfect. To help our government customers and organizations in government-regulated industries, we are […]

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 […]

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 […]

Factorization machines can be used for classification or regression and are much more computationally efficient on large sparse data sets than traditional algorithms like linear regression. This property is why FM are widely used for recommendation.

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 […]

April 2023 Update: Starting January 31, 2024, you will no longer be able to access AWS DeepLens through the AWS management console, manage DeepLens devices, or access any projects you have created. To learn more, refer to these frequently asked questions about AWS DeepLens end of life. Yesterday we announced the integration of AWS DeepLens with […]

August 2021: Post updated with changes required for SageMaker SDK v2, courtesy of Eitan Sela, Senior Startup Solutions Architect 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 […]

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 […]

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 […]