AWS Machine Learning Blog

Category: Artificial Intelligence

Alexa uses Amazon Translate to reach more international customers

Amazon Alexa is available in 15 locales and eight languages. To understand and respond in different languages, Alexa needs to learn new grammar rules, and the content that powers Alexa needs to be translated to new languages. Additionally, Alexa needs to learn about country-specific topics, such as new soccer leagues, regional celebrities, and important historical […]

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Amazon Textract is now SOC and ISO compliant

You can now use Amazon Textract, a machine learning (ML) service that quickly and easily extracts text and data from forms and tables in scanned documents, for workloads that are subject to Service Organization Control (SOC) compliance and International Organization for Standardization (ISO) compliance. This launch builds upon the existing portfolio of AWS ML services […]

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Creating a music genre model with your own data in AWS DeepComposer

AWS DeepComposer is an educational AWS service that teaches generative AI and uses Generative Adversarial Networks (GANs) to transform a melody that you provide into a completely original song. With AWS DeepComposer, you can use one of the pre-trained music genre models (such as Jazz, Rock, Pop, Symphony, or Jonathan-Coulton) or train your own. As […]

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Designing human review workflows with Amazon Translate and Amazon Augmented AI

The world is becoming smaller as many businesses and organizations expand globally. As businesses expand their reach to wider audiences across different linguistic groups, their need for interoperability with multiple languages increases exponentially. Most of the industry work is manual, slow, and expensive human effort, with many industry verticals struggling to find a scalable, reliable, […]

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Implementing hyperparameter optimization with Optuna on Amazon SageMaker

Preferred Networks (PFN) released the first major version of their open-source hyperparameter optimization (HPO) framework Optuna in January 2020, which has an eager API. This post introduces a method for HPO using Optuna and its reference architecture in Amazon SageMaker. Amazon SageMaker supports various frameworks and interfaces such as TensorFlow, Apache MXNet, PyTorch, scikit-learn, Horovod, Keras, […]

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Train ALBERT for natural language processing with TensorFlow on Amazon SageMaker

At re:Invent 2019, AWS shared the fastest training times on the cloud for two popular machine learning (ML) models: BERT (natural language processing) and Mask-RCNN (object detection). To train BERT in 1 hour, we efficiently scaled out to 2,048 NVIDIA V100 GPUs by improving the underlying infrastructure, network, and ML framework. Today, we’re open-sourcing the optimized training code for […]

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Creating a complete TensorFlow 2 workflow in Amazon SageMaker

Managing the complete lifecycle of a deep learning project can be challenging, especially if you use multiple separate tools and services. For example, you may use different tools for data preprocessing, prototyping training and inference code, full-scale model training and tuning, model deployments, and workflow automation to orchestrate all of the above for production. Friction […]

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Gain customer insights using Amazon Aurora machine learning

In recent years, AWS customers have been running machine learning (ML) on an increasing variety of datasets and data sources. Because a large percentage of organizational data is stored in relational databases such as Amazon Aurora, there’s a common need to make this relational data available for training ML models, and to use ML models […]

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AWS Machine Learning Scholarship Program from Udacity is now open for enrollment

Developers, to help you advance your AI and machine learning (ML) skills with hands-on and engaging learning, the AWS Machine Learning Scholarship Program from Udacity is now open for enrollment. AWS and Udacity are collaborating to educate developers of all skill levels to expand their AWS ML expertise. In this scholarship program, all eligible students […]

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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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