A Technology Broker and Management Company Specializing in KM Systems
Favorite In computer vision, semantic segmentation is the task of classifying every pixel in an image with a class from a known set of labels such that pixels with the same label share certain characteristics. It generates a segmentation mask of the input images. For example, the following images show
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Shared by AWS Machine Learning June 28, 2022
Favorite Amazon SageMaker provides a suite of built-in algorithms, pre-trained models, and pre-built solution templates to help data scientists and machine learning (ML) practitioners get started on training and deploying ML models quickly. You can use these algorithms and models for both supervised and unsupervised learning. They can process various
Read More Shared by AWS Machine Learning June 28, 2022
Favorite Amazon Polly is a leading cloud-based service that converts text into lifelike speech. Following the adoption of Neural Text-to-Speech (NTTS), we have continuously expanded our portfolio of available voices in order to provide a wide selection of distinct speakers in supported languages. Today, we are pleased to announce four
Read More Shared by AWS Machine Learning June 28, 2022
Favorite Launched at AWS re:Invent 2021, Amazon SageMaker Ground Truth Plus helps you create high-quality training datasets by removing the undifferentiated heavy lifting associated with building data labeling applications and managing the labeling workforce. All you do is share data along with labeling requirements, and Ground Truth Plus sets up
Read More Shared by AWS Machine Learning June 27, 2022
Favorite Pride is an interesting motivator in Knowledge Management. In some cases it acts as a real dis-incentive, but if harnessed well it can be a powerful driver for KM behaviours. Proud Lion from Public Domain Pictures I was reflecting on this recently while running one of our powerful Bird Island
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Shared by Nick Milton June 27, 2022
Favorite Running machine learning (ML) experiments in the cloud can span across many services and components. The ability to structure, automate, and track ML experiments is essential to enable rapid development of ML models. With the latest advancements in the field of automated machine learning (AutoML), namely the area of
Read More Shared by AWS Machine Learning June 24, 2022
Favorite We are excited to announce Amazon CodeWhisperer, a machine learning (ML)-powered service that helps improve developer productivity by providing code recommendations based on developers’ natural comments and prior code. With CodeWhisperer, developers can simply write a comment that outlines a specific task in plain English, such as “upload a
Read More Shared by AWS Machine Learning June 24, 2022
Favorite As enterprise businesses embrace machine learning (ML) across their organizations, manual workflows for building, training, and deploying ML models tend to become bottlenecks to innovation. To overcome this, enterprises needs to shape a clear operating model defining how multiple personas, such as data scientists, data engineers, ML engineers, IT,
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Favorite In a previous post, we talked about analyzing and tagging assets stored in Veeva Vault PromoMats using Amazon AI services and the Veeva Vault Platform’s APIs. In this post, we explore how to use Amazon AppFlow, a fully managed integration service that enables you to securely transfer data from
Read More Shared by AWS Machine Learning June 24, 2022
Favorite This blog post is co-authored by Guillermo Ribeiro, Sr. Data Scientist at Cepsa. Machine learning (ML) has rapidly evolved from being a fashionable trend emerging from academic environments and innovation departments to becoming a key means to deliver value across businesses in every industry. This transition from experiments in
Read More Shared by AWS Machine Learning June 24, 2022