2015 AWS ML 
AWS Machine Learning Blog
DECEMBER 4, 2023
Established in 2015, Getir has positioned itself as the trailblazer in the sphere of ultrafast grocery delivery. In this post, we explain how we built an end-to-end product category prediction pipeline to help commercial teams by using Amazon SageMaker and AWS Batch , reducing model training duration by 90%.
AWS Machine Learning Blog
DECEMBER 7, 2023
Getir was founded in 2015 and operates in Turkey, the UK, the Netherlands, Germany, and the United States. In this post, we describe the end-to-end workforce management system that begins with location-specific demand forecast, followed by courier workforce planning and shift assignment using Amazon Forecast and AWS Step Functions.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
AWS Machine Learning Blog
JANUARY 13, 2023
To mitigate these challenges, we propose a federated learning (FL) framework, based on open-source FedML on AWS, which enables analyzing sensitive HCLS data. It involves training a global machine learning (ML) model from distributed health data held locally at different sites.
AWS Machine Learning Blog
APRIL 25, 2024
The most common techniques used for extractive summarization are term frequency-inverse document frequency (TF-IDF), sentence scoring, text rank algorithm, and supervised machine learning (ML). Hurricane Patricia has been rated as a categor… Human: 23 October 2015 Last updated at 17:44 B… [{‘name’: meteor’, “value’: 0.102339181286549.
AWS Machine Learning Blog
SEPTEMBER 29, 2023
In late 2023, Planet announced a partnership with AWS to make its geospatial data available through Amazon SageMaker. In this post, we illustrate how to use a segmentation machine learning (ML) model to identify crop and non-crop regions in an image. Planet’s data is therefore a valuable resource for geospatial ML.
AWS Machine Learning Blog
FEBRUARY 24, 2023
AWS recently released Amazon SageMaker geospatial capabilities to provide you with satellite imagery and geospatial state-of-the-art machine learning (ML) models, reducing barriers for these types of use cases. For more information, refer to Preview: Use Amazon SageMaker to Build, Train, and Deploy ML Models Using Geospatial Data.
AWS Machine Learning Blog
FEBRUARY 28, 2023
In today’s highly competitive market, performing data analytics using machine learning (ML) models has become a necessity for organizations. For example, in the healthcare industry, ML-driven analytics can be used for diagnostic assistance and personalized medicine, while in health insurance, it can be used for predictive care management.
Expert insights. Personalized for you.
119 
Let's personalize your content