AWS Machine Learning

Amazon S3 plugin for PyTorch is an open-source library which is built to be used with the deep learning framework PyTorch for streaming data from Amazon Simple Storage Service (Amazon S3). With this feature […]

AWS DeepRacer is the fastest way to get rolling with machine learning (ML) through a global racing league, cloud-based 3D racing simulator, and fully autonomous 1/18th scale race car driven by reinforcement […]

Many universities like transcribing their recorded class lectures and later creating captions out of these transcriptions. Amazon Transcribe is a fully-managed automatic speech recognition service (ASR) that makes […]

You can use various tools to define and run machine learning (ML) pipelines or DAGs (Directed Acyclic Graphs). Some popular options include AWS Step Functions, Apache Airflow, KubeFlow Pipelines (KFP), TensorFlow […]

The Intel Olympic Technology Group (OTG), a division within Intel focused on bringing cutting-edge technology to Olympic athletes, collaborated with AWS Machine Learning Professional Services (MLPS) to build a […]

Data scientists can spend up to 80% of their time preparing data for machine learning (ML) projects. This preparation process is largely undifferentiated and tedious work, and can involve multiple programming APIs […]

Running machine learning (ML) models at the edge can be a powerful enhancement for Internet of Things (IoT) solutions that must perform inference without a constant connection back to the cloud. Although there are […]

Machine learning (ML) is highly iterative and complex in nature, and requires data scientists to explore multiple ways in which a business problem can be solved. Data scientists have to use tools that support […]

The last few years have seen the rise of transformer deep learning architectures to build natural language processing (NLP) model families. The adaptations of the transformer architecture in models such as BERT, […]

This is a guest post from Mikael Graindorge, Sales Operations Leader at Thermo Fisher Scientific.
In the life sciences industry, data is growing in abundance and is getting increasingly complex, which makes it […]

With the number of cameras and sensors deployed growing exponentially, companies across industries are consuming more video than ever before. Additionally, advancements in analytics have expanded potential use […]

We are excited to announce Aria, Amazon Polly’s first New Zealand English Neural text-to-speech (NTTS) voice. Similar to other Amazon Polly voices, Aria is developed as a voice that sounds bright, natural, and u […]

The celebrity recognition feature in Amazon Rekognition automatically recognizes tens of thousands of well-known personalities in images and videos using machine learning (ML). Celebrity recognition significantly […]

With Amazon SageMaker Pipelines, you can create, automate, and manage end-to-end machine learning (ML) workflows at scale. SageMaker Projects build on SageMaker Pipelines by providing several MLOps templates that […]

Multiple pieces of information are often required to complete a task or to process a query. For example, when talking to an insurance agent, a caller might ask, “Can you provide me quotes for home, auto, and b […]

Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning. It provides a single, web-based visual interface where you can perform all ML development steps required to […]

Amazon SageMaker Studio is a web-based, integrated development environment (IDE) for machine learning (ML) that lets you build, train, debug, deploy, and monitor your ML models.
Although Studio provides all the […]

In Part 1 of this series of posts, we offered step-by-step guidance for using Amazon SageMaker, SageMaker projects and Amazon SageMaker Pipelines, and AWS services such as Amazon Virtual Private Cloud (Amazon […]

Today, we’re excited to announce that Amazon SageMaker notebook instances support Amazon Linux 2. You can now choose Amazon Linux 2 for your new SageMaker notebook instance to take advantage of the latest update a […]

Amazon SageMaker notebook instances now support Amazon Linux 2, so you can now create a new Amazon SageMaker notebook instance to start developing your machine learning (ML) models with the latest updates. An […]