AWS Machine Learning Blog

Build an Amazon Lex Chatbot with Microsoft Excel

This is a guest post by AWS Community Hero Cyrus Wong. Our institution (IVE) here in Hong Kong has begun experimenting with Amazon Lex in teaching, research, and healthcare. We have many non-technical employees, such as English teachers in IVE and therapists from IVE Childcare, Elderly and Community Services Discipline, who don’t have the technical […]

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Making neural nets uncool again – AWS style

by Jeremy Howard and Joseph Spisak | on | in SageMaker | Permalink | Comments |  Share

Just as the goal of Amazon AI is to democratize machine learning with the development of platforms such as Amazon SageMaker, the goal of fast.ai is to level the educational playing field so that anyone can pick up machine learning and be productive. The fast.ai tagline is “Making neural nets uncool again.” This is not a play to decrease the popularity of deep neural networks, but instead to broaden their appeal and accessibility beyond the academic elites who have dominated the research in this area.

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AWS CloudTrail integration is now available in Amazon SageMaker

AWS customers have been requesting a way to log activity in Amazon SageMaker, to help you meet your governance and compliance needs. I’m happy to announce that Amazon SageMaker is now integrated with AWS CloudTrail, a service that enables you to log, continuously monitor, and retain account information related to Amazon SageMaker API activity. Amazon […]

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Now available in Amazon SageMaker: DeepAR algorithm for more accurate time series forecasting

by Tim Januschowski, David Arpin, David Salinas, Valentin Flunkert, Jan Gasthaus, Lorenzo Stella, and Paul Vazquez | on | in SageMaker | Permalink | Comments |  Share

Today we are launching Amazon SageMaker DeepAR as the latest built-in algorithm for Amazon SageMaker. DeepAR is a supervised learning algorithm for time series forecasting that uses recurrent neural networks (RNN) to produce both point and probabilistic forecasts. We’re excited to give developers access to this scalable, highly accurate forecasting algorithm that drives mission-critical decisions within Amazon. Just as […]

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Build Amazon SageMaker notebooks backed by Spark in Amazon EMR

Introduced at AWS re:Invent in 2017, Amazon SageMaker provides a fully managed service for data science and machine learning workflows. One of the important parts of Amazon SageMaker is the powerful Jupyter notebook interface, which can be used to build models. You can enhance the Amazon SageMaker capabilities by connecting the notebook instance to an […]

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How to Deploy Deep Learning Models with AWS Lambda and Tensorflow

Deep learning has revolutionized how we process and handle real-world data. There are many types of deep learning applications, including applications to organize a user’s photo archive, make book recommendations, detect fraudulent behavior, and perceive the world around an autonomous vehicle. In this post, we’ll show you step-by-step how to use your own custom-trained models […]

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Now Available: New Digital Training to Help You Learn About Machine Learning and Artificial Intelligence on AWS

by Sara Snedeker | on | Permalink | Comments |  Share

AWS Training and Certification recently released free digital training courses that will make it easier for you to build your cloud skills and learn about machine learning (ML) and artificial intelligence (AI). This includes new courses like Introduction to Deep Learning and Introduction to Amazon SageMaker. You can get free and unlimited access to more than 100 new […]

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AWS Deep Learning AMIs Now Available in 4 New Regions: Beijing, Frankfurt, Singapore, and Mumbai

The AWS Deep Learning AMIs are now available in four new AWS Regions: China (Beijing) operated by Sinnet, Europe (Frankfurt), Asia Pacific (Singapore), and Asia Pacific (Mumbai). The Amazon Machine Images (AMIs) provide provide machine learning practitioners with the infrastructure and tools to accelerate deep to quickly start experimenting with deep learning models. The AMIs […]

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Leveraging Low Precision and Quantization for Deep Learning Using the Amazon EC2 C5 Instance and BigDL  

by Jason Dai and Joseph Spisak | on | Permalink | Comments |  Share

Recently AWS released the new compute-intensive Amazon EC2 C5 instances, based on the latest generation Intel Xeon Scalable Platinum processors. These instances are designed for compute-heavy applications, and offer a large performance improvement over the C4 instances. They also have additional memory per vCPU, and twice the performance for vector and floating-point workloads. In this […]

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Congratulations to the Winners of the re:Invent Robocar Rally 2017!

To drive awareness of deep learning, machine learning, and the internet of things in autonomous driving, AWS hosted a hackathon—the Robocar Rally—at re:Invent in November 2017. We kicked off Robocar Rally in September with a series of blog posts and Twitch streams. At re:Invent, we had 100 attendees come for a hands-on two-day hackathon using deep learning and the open source Donkey Car platform with AWS machine learning services and AWS IoT. They formed teams, and built, customized, trained, and raced their own 1/16th scale cars. There’s a lot we could talk about, but we think this video shows the event better than we could write about it.

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