AWS Machine Learning

In this post, we show you how to select the right metadata for your use case when building a recommendation engine using Amazon Personalize. The aim is to help you optimize your models to generate more […]

In recent years, businesses are increasingly looking for ways to integrate the power of machine learning (ML) into business decision-making. This post demonstrates the use case of creating an optimal incentive […]

Optical character recognition (OCR) technology, which enables extracting text from an image, has been around since the mid-20th century, and continues to be a research topic today. OCR and document understanding […]

University of Illinois, Urbana Champaign (UIUC) has partnered with the Amazon Machine Learning Solutions Lab to help UIUC football coaches prepare for games more efficiently and improve their odds of winning. […]

Live video streams are continuously generated across industries including media and entertainment, retail, and many more. Live events like sports, music, news, and other special events are broadcast for viewers on […]

In April 2020, AWS and Facebook announced the launch of TorchServe to allow researches and machine learning (ML) developers from the PyTorch community to bring their models to production more quickly and without […]

The volume of user-generated content (UGC) and third-party content has been increasing substantially in sectors like social media, ecommerce, online advertising, and photo sharing. However, such content needs to […]

Amazon Comprehend is a natural language processing (NLP) service that uses machine learning (ML) to find insights and relationships like people, places, sentiments, and topics in unstructured text. You can now use […]

AWS is excited to announce the winner of the second AWS DeepComposer Chartbusters challenge, Lena Taupier. AWS DeepComposer gives developers a creative way to get started with machine learning (ML). In June, we […]

In an effort to drive customer service improvements, many companies record the phone conversations between their customers and call center representatives. These call recordings are typically stored as audio files […]

Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. Amazon SageMaker removes the heavy […]

Amazon Personalize is a machine learning (ML) service that enables you to personalize your website, app, ads, emails, and more with private, custom ML models that you can create with no prior ML experience. […]

The new Amazon SageMaker Studio Image Build convenience package allows data scientists and developers to easily build custom container images from your Studio notebooks via a new CLI. The new CLI eliminates the […]

Amazon SageMaker is a fully managed service that allows you to build, train, deploy, and monitor machine learning (ML) models. Its modular design allows you to pick and choose the features that suit your use cases […]

This is a guest post by Anthony Sabelli, Head of Data Science at Kabbage, a data and technology company providing small business cash flow solutions.
Kabbage is a data and technology company providing small […]

This post is written in collaboration with DevFactory, an AWS Select Technology Partner.
DevFactory is an enterprise SaaS-focused company that is responsible for innovation, development, and operation of over 120 […]

This guest post was authored by Kazuma Ohara, Director of RENGA Inc., and edited by Yumiko Kanasugi, Solutions Architect at AWS Japan.
RENGA Inc. operates Mansion Note, one of Japan’s most popular condominium r […]

When machine learning (ML) is deployed in production, monitoring the model is important for maintaining the quality of predictions. Although the statistical properties of the training data are known in advance, […]

TensorBoard is an open-source toolkit for TensorFlow users that allows you to visualize a wide range of useful information about your model, from model graphs; to loss, accuracy, or custom metrics; to embedding […]

In 1993, the Portable Document Format or the PDF was born and released to the world. Since then, companies across various industries have been creating, scanning, and storing large volumes of documents in this […]