Category: Amazon SageMaker

Building, training, and deploying machine learning models from scratch can be a time-consuming and costly endeavor for some customers. Moreover, once deployed to production, machine learning models need to be continuously monitored for deviations in model and data quality. To help you expedite model deployment and implement a model monitoring solution, you can integrate pre-trained […]

New deep-learning model architectures push what’s possible in the field of natural language processing (NLP). NLP is the study of methods of processing and analysis of human language data. In machine learning (ML), transfer learning takes model parameters learned on one task and uses them as a basis for another task with some additional fine-tuning. […]

Pre-trained machine learning (ML) models available in AWS Marketplace take care of the heavy lifting, helping you deliver Artificial Intelligence (AI)- and ML-powered features faster and at a lower cost. However, just like all ML models, sometimes ML model predictions are just not confident enough. You want a pair of human eyes to confirm the […]

This is the second article of a two-part series. Part 1 covered data preparation for machine learning (ML) by using Trifacta. Part 2 covers training the model using Amazon SageMaker Autopilot and operationalizing the workflow. Background ML provides value to business by offering accurate insights to guide business decisions. Gathering insights from ML should be […]

Here are AWS Marketplace sessions you can register for and view at re:Invent this week! Each session is held three times, in Pacific Standard Time (PST), Singapore Standard Time (SST), and London Greenwich Mean Time (GMT) time zones. Be sure to check the linked catalog listing, as dates and times may change. MKT208: Use data […]

Recently, AWS announced the release of TorchServe, a PyTorch open-source project in collaboration with Facebook. PyTorch is an open-source machine learning framework created by Facebook, which is popular among ML researchers and data scientists. Despite its ease of use and “Pythonic” interface, deploying and managing models in production is still difficult as it requires data scientists to […]

By guest authors Anton Chudaev, DevOps Competence Manager at VITech, Yevheniia Minaieva, Product marketing lead at VITech Lab, and Dmitry Spodarets, Head of VITech Lab When managing Personal Protective Equipment (PPЕ) compliance, temporary absence of safety engineers and human fatigue can lead to unnoticed safety rule breaches. VITech Lab offers a solution to help healthcare […]

During my interactions, I hear feedback from builders on how they are looking to test drive machine learning (ML) models quickly. AWS Marketplace makes it easy to find, try, buy, and deploy ML models, which are deployed using Amazon SageMaker. I’m pleased to announce that the Try Product demo feature is now available. This feature lets […]

This post describes winning solutions from the AWS Marketplace Machine Learning Challenge hackathon. Other winners created solutions using machine learning to stay connected and to automate tasks and increase personalization. Introduction The AWS Marketplace Machine Learning (ML) team recently hosted a ML hackathon on The DevPost Platform, AWS Marketplace Developer Challenge: ML-Powered Solutions. A hackathon […]

This post describes winning solutions from the AWS Marketplace Machine Learning Challenge hackathon. Other winners created solutions using machine learning to stay connected and to support healthcare during a pandemic. Introduction During spring 2020, the AWS Marketplace Developer Challenge: ML Powered Solutions hackathon put forth a test for builders all over the world. The challenge […]