A Technology Broker and Management Company Specializing in KM Systems
Favorite Amazon SageMaker is a fully managed service that provides every machine learning (ML) developer and data scientist the ability to build, train, and deploy ML models at scale. Amazon SageMaker Studio is a web-based, integrated development environment (IDE) for ML. Amazon SageMaker Studio provides all the tools you need
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Shared by AWS Machine Learning October 28, 2021
Favorite One of the main challenges in a machine learning (ML) project implementation is the variety and high number of development artifacts and tools used. This includes code in notebooks, modules for data processing and transformation, environment configuration, inference pipeline, and orchestration code. In production workloads, the ML model created
Read More Shared by AWS Machine Learning October 28, 2021
Favorite This post was created in collaboration with Mohammed Alauddin, Data Engineering and Data Science Regional Manager, and Kamal Hossain, Lead Data Scientist at iProperty.com.my, now part of PropertyGuru Group. iProperty.com.my is the market-leading property portal in Malaysia and is now part of the PropertyGuru Group. iProperty.com.my offers a search
Read More Shared by AWS Machine Learning October 28, 2021
Favorite Here is a link to a video of my ex-colleague Rupert Lescott talking at a virtual KM event about the application of KM to projects within PWC. Thanks Rupert for letting me share the link below (you will need to ckick the link rather than the picture. PWC Case
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Shared by Nick Milton October 27, 2021
Favorite Feature engineering is expensive and time-consuming, which may lead you to adopt a feature store for managing features across teams and models. Unfortunately, machine learning (ML) lineage solutions have yet to adapt to this new concept of feature management. To achieve the full benefits of a feature store by
Read More Shared by AWS Machine Learning October 27, 2021
Favorite Amazon Fraud Detector is a fully managed service that makes it easy to identify potentially fraudulent online activities, such as the creation of fake accounts or online payment fraud. Amazon Fraud Detector uses machine learning (ML) under the hood and is based on over 20 years of fraud detection
Read More Shared by AWS Machine Learning October 27, 2021
Favorite Knowledge is both an input to, and an output from, project activity. The projects therefore need a plan to manage that knowledge. Projects consume and create resources. They consume money, time and equipment, and they create products and income streams. They also consume (or, rather, access and apply) knowledge
Read More Shared by Nick Milton October 25, 2021
Favorite Amazon SageMaker JumpStart helps you quickly and easily get started with machine learning (ML) and provides a set of solutions for the most common use cases that can be trained and deployed readily with just a few clicks. JumpStart also includes a collection of multimodal financial text analysis tools,
Read More Shared by AWS Machine Learning October 23, 2021
Favorite In this post, you will learn how to create a multi-branch training MLOps continuous integration and continuous delivery (CI/CD) pipeline using AWS CodePipeline and AWS CodeCommit, in addition to Jenkins and GitHub. I discuss the concept of experiment branches, where data scientists can work in parallel and eventually merge
Read More Shared by AWS Machine Learning October 23, 2021
Favorite Defect detection in manufacturing can benefit from machine learning (ML) and computer vision (CV) to reduce operational costs, improve time to market, and increase productivity, quality, and safety. According to McKinsey, the “benefits of defect detection and other Industry 4.0 applications are estimated to create a potential value of
Read More Shared by AWS Machine Learning October 23, 2021