Remove 2023 Remove Clustering Remove ML
article thumbnail

Racing into the future: How AWS DeepRacer fueled my AI and ML journey

AWS Machine Learning Blog

At the time, I knew little about AI or machine learning (ML). But AWS DeepRacer instantly captured my interest with its promise that even inexperienced developers could get involved in AI and ML. Panic set in as we realized we would be competing on stage in front of thousands of people while knowing little about ML.

AWS 108
article thumbnail

Map Earth’s vegetation in under 20 minutes with Amazon SageMaker

AWS Machine Learning Blog

Amazon SageMaker supports geospatial machine learning (ML) capabilities, allowing data scientists and ML engineers to build, train, and deploy ML models using geospatial data. We pick the first week of December 2023 in this example. This way, our analysis is based on clear and reliable imagery.

ML 113
professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

PEFT fine tuning of Llama 3 on SageMaker HyperPod with AWS Trainium

AWS Machine Learning Blog

The process of setting up and configuring a distributed training environment can be complex, requiring expertise in server management, cluster configuration, networking and distributed computing. To simplify infrastructure setup and accelerate distributed training, AWS introduced Amazon SageMaker HyperPod in late 2023.

AWS 105
article thumbnail

Real value, real time: Production AI with Amazon SageMaker and Tecton

AWS Machine Learning Blog

Businesses are under pressure to show return on investment (ROI) from AI use cases, whether predictive machine learning (ML) or generative AI. Only 54% of ML prototypes make it to production, and only 5% of generative AI use cases make it to production. Using SageMaker, you can build, train and deploy ML models.

ML 95
article thumbnail

Open source observability for AWS Inferentia nodes within Amazon EKS clusters

AWS Machine Learning Blog

Recent developments in machine learning (ML) have led to increasingly large models, some of which require hundreds of billions of parameters. In such distributed environments, observability of both instances and ML chips becomes key to model performance fine-tuning and cost optimization. or later NPM version 10.0.0

AWS 125
article thumbnail

Create Audience Segments Using K-Means Clustering, Churn Prevention with Reinforcement Learning…

ODSC - Open Data Science

Volunteer for ODSC East 2023 ODSC volunteers are an integral part of the success of each ODSC conference and a perfect extension of our core team and ambassadors to our community! The final step is to implement and monitor the solution, refining it over time to ensure it delivers the desired outcomes.

article thumbnail

MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

As you delve into the landscape of MLOps in 2023, you will find a plethora of tools and platforms that have gained traction and are shaping the way models are developed, deployed, and monitored. Open-source tools have gained significant traction due to their flexibility, community support, and adaptability to various workflows.