AWS Machine Learning Blog

Category: SageMaker

Create high-quality instructions for Amazon SageMaker Ground Truth labeling jobs

Amazon SageMaker Ground Truth helps you quickly build highly accurate training datasets for machine learning (ML). You can use your own workers, a choice of vendor-managed workforces that specialize in data labeling, or a public workforce powered by Amazon Mechanical Turk to provide the human-generated labels. To get high-quality labels, you must provide simple, concise, […]

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Build a serverless anomaly detection tool using Java and the Amazon SageMaker Random Cut Forest algorithm

One of the problems that business owners commonly face is detecting when something unusual is happening in their business. Detecting unusual user activity or changes in daily traffic patterns are just some of the challenges. With an ever-increasing amount of data and metrics, detecting anomalies with the help of machine learning is a great way […]

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Control root access to Amazon SageMaker notebook instances

Amazon SageMaker recently introduced the ability to enable and disable root access for notebook users. Before I give you a preview of how you can implement this new feature using the AWS Management Console and Amazon SageMaker API actions, I’ll explain why controlling root access for users is helpful. Amazon SageMaker provides fully managed notebook […]

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Become a certified machine learning developer with the new AWS Certified Machine Learning – Specialty certification

Back in November 2018 we announced on this blog that the same machine learning (ML) courses used to train engineers at Amazon are now available to all developers through AWS. Today, we’re letting you know that there is a way to enhance and validate your ability to build, train, tune, and deploy machine learning models […]

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Bring your own hyperparameter optimization algorithm on Amazon SageMaker

In this blog post, we’ll discuss how to implement custom, state-of-the-art hyperparameter optimization (HPO) algorithms to tune models on Amazon SageMaker. Amazon SageMaker includes a built-in HPO algorithm, but provides the flexibility to use your own HPO algorithm. We’ll provide you with a framework to incorporate an HPO algorithm that you choose. However, before we […]

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Easily perform bulk label quality assurance using Amazon SageMaker Ground Truth

In this blog post we’re going to walk you through an example situation where you’ve just built a machine learning system that labels your data at volume and you want to perform manual quality assurance (QA) on some of the labels. How can you do so without overwhelming your limited resources?  We’ll show you how, […]

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Use two additional data labeling services for your Amazon SageMaker Ground Truth labeling jobs

We’re excited to announce the availability of two more data labeling services that you can use for your Amazon SageMaker Ground Truth labeling jobs: Data Labeling Services by iMerit’s US-based workforce Data Labeling Services by Startek, Inc. These new listings on the AWS Marketplace supplement the existing iMerit India-based workforce listing to provide you a […]

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Preprocess input data before making predictions using Amazon SageMaker inference pipelines and Scikit-learn

Amazon SageMaker enables developers and data scientists to build, train, tune, and deploy machine learning (ML) models at scale. You can deploy trained ML models for real-time or batch predictions on unseen data, a process known as inference. However, in most cases, the raw input data must be preprocessed and can’t be used directly for […]

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Identifying bird species on the edge using the Amazon SageMaker built-in Object Detection algorithm and AWS DeepLens

Custom object detection has become an important enabler for a wide range of industries and use cases—such as finding tumors in MRIs, identifying diseased crops, and monitoring railway platforms. In this blog post, we build a bird identifier based on an annotated public dataset. This type of model could be used in a number of […]

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Creating hierarchical label taxonomies using Amazon SageMaker Ground Truth

At re:Invent 2018 we launched Amazon SageMaker Ground Truth, which can Build Highly Accurate Datasets and Reduce Labeling Costs by up to 70% using machine learning. Amazon SageMaker Ground Truth offers easy access to public and private human labelers and provides them with built-in workflows and interfaces for common labeling tasks. Additionally, Amazon SageMaker Ground […]

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