AWS Machine Learning Blog

Category: AWS Batch

How Getir reduced model training durations by 90% with Amazon SageMaker and AWS Batch

This is a guest post co-authored by Nafi Ahmet Turgut, Hasan Burak Yel, and Damla Şentürk from Getir. Established in 2015, Getir has positioned itself as the trailblazer in the sphere of ultrafast grocery delivery. This innovative tech company has revolutionized the last-mile delivery segment with its compelling offering of “groceries in minutes.” With a […]

Machine learning inference at scale using AWS serverless

With the growing adoption of Machine Learning (ML) across industries, there is an increasing demand for faster and easier ways to run ML inference at scale. ML use cases, such as manufacturing defect detection, demand forecasting, fraud surveillance, and many others, involve tens or thousands of datasets, including images, videos, files, documents, and other artifacts. […]

Build an online compound solubility prediction workflow with AWS Batch and Amazon SageMaker

Machine learning (ML) methods for the field of computational chemistry are growing at an accelerated rate. Easy access to open-source solvers (such as TensorFlow and Apache MXNet), toolkits (such as RDKit cheminformatics software), and open-scientific initiatives (such as DeepChem) makes it easy to use these frameworks in daily research. In the field of chemical informatics, many […]

Create Audiobooks with Amazon Polly and AWS Batch

Update: On 17 JUL 2018, Amazon Polly released Asynchronous Synthesis, a new feature that enables you to process up to 100,000 characters of text at a time using asynchronous requests. Read this article for details: Amazon Polly Update – Time-Driven Prosody and Asynchronous Synthesis. Amazon Polly, one of AWS’s first AI services, turns text into lifelike […]