AWS Machine Learning

Autonomous vehicle companies typically use LiDAR sensors to generate a 3D understanding of the environment around their vehicles. For example, they mount a LiDAR sensor on their vehicles to continuously capture […]

This is a guest post by Jeff McKelvey, Principal Development Lead at HiConversion. The team at HiConversion has collaborated closely with James Jory, Applied AI Services Solutions Architect at AWS, and Matt […]

This is a guest post by Cyrus Wong, an AWS Machine Learning Hero. You can learn more about and connect with AWS Machine Learning Heroes at the community page. 
On July 29, 2020, AWS announced that Amazon […]

AWS DeepRacer is the fastest way to get started with machine learning (ML). You can train reinforcement learning (RL) models by using a 1/18th scale autonomous vehicle in a cloud-based virtual simulator and […]

We’re back with two new challenges for the AWS DeepComposer Chartbusters 2021 season! Chartbusters is a global challenge in which developers use AWS DeepComposer to create original compositions and compete in m […]

Processing large documents like PDFs and static images is a cornerstone of today’s highly regulated industries. From healthcare information like doctor-patient visits and bills of health, to financial documents l […]

In industrial IoT, running machine learning (ML) models on edge devices is necessary for many use cases, such as predictive maintenance, quality improvement, real-time monitoring, process optimization, and […]

This post was guest authored by AWS Advanced Consulting Partner Quantiphi.
The mortgage industry is highly complex and largely dependent on documents for the information required across different stages in their […]

Determining the relevance of a sentence when compared to a specific document is essential for many different types of applications across various industries. In this post, we focus on a use case within the […]

Data quality is an important topic for virtually all teams and systems deriving insights from data, especially teams and systems using machine learning (ML) models. Supervised ML is the task of learning a function […]

Amazon Lookout for Vision is a machine learning (ML) service that spots defects and anomalies in visual representations using computer vision (CV). With Amazon Lookout for Vision, manufacturing companies can […]

Amazon Forecast now displays the estimated time it takes to complete an in-progress workflow for importing your data, training the predictor, and generating the forecast. You can now manage your time more […]

Medical providers often need to analyze and dictate patient phone conversations, doctors’ notes, clinical trial reports, and patient health records. By automating transcription, providers can quickly and a […]

Amazon SageMaker Studio is a web-based fully integrated development environment (IDE) where you can perform end-to-end machine learning (ML) development to prepare data and build, train, and deploy models.
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Want to accelerate machine learning (ML) innovation in your organization? Join us for 30 days of new Amazon SageMaker content designed to help you build, train, and deploy ML models faster. On April 20, we’re k […]

You can now control the Amazon Virtual Private Cloud (Amazon VPC) and encryption settings for your Amazon Comprehend APIs using AWS Identity and Access Management (IAM) condition keys, and encrypt your Amazon […]

Customers often ask us how can they lower their costs when conducting deep learning training on AWS. Training deep learning models with libraries such as TensorFlow, PyTorch, and Apache MXNet usually requires […]

In preparation for the upcoming Olympic Games, Intel®, an American multinational corporation and one of the world’s largest technology companies, developed a concept around 3D Athlete Tracking (3DAT). 3DAT is a ma […]

Today, we’re pleased to launch Machine Learning Essentials for Business and Technical Decision Makers—a series of three free, on-demand, digital-training courses from AWS Training and Certification. These cou […]

Amazon SageMaker Data Wrangler is the fastest and easiest way for data scientists to prepare data for machine learning (ML) applications. With Data Wrangler, you can simplify the process of feature engineering and […]