Tag: Amazon SageMaker
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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....
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,...
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 […]
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...
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...
Omnichannel personalization with Amazon Personalize
As the touchpoints customers use to engage with brands move to an increasingly complex mixture of digital and real-life interactions, you’re faced with the daunting task of delighting your customers with personalized experiences that hit the mark across these channels. Customer expectations are evolving as well. Today’s customers quickly lose patience with brands that can’t […]
Building a lawn monitor and weed detection solution with AWS machine learning and IoT services
For new home buyers, a common challenge is to understand how to manage their lawn needs effectively. Now imagine if you’re a farmer...
Learn how to select ML instances on the fly in Amazon SageMaker Studio
Amazon Web Services (AWS) is happy to announce the general availability of Notebooks within Amazon SageMaker Studio. Amazon SageMaker Studio supports on-the-fly selection...
ML Explainability with Amazon SageMaker Debugger
Machine Learning (ML) impacts industries around the globe, from financial services industry (FSI) and manufacturing to autonomous vehicles and space exploration. ML is no longer just an aspirational technology exclusive to academic and research institutions; it has evolved into a mainstream technology that has the potential to benefit organizations of all sizes. However, a lack […]
Scaling your AI-powered Battlesnake with distributed reinforcement learning in Amazon SageMaker
Battlesnake is an AI competition in which you build AI-powered snakes. Battlesnake’s rules are similar to the traditional snakes game. Your goal is...
Amazon A2I is now generally available
AWS is excited to announce the general availability of Amazon Augmented AI (Amazon A2I), a new service that makes it easy to implement...
Announcing availability of Inf1 instances in Amazon SageMaker for high performance and cost-effective machine learning inference
Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine...