Favorite High-quality machine learning (ML) models depend on accurately labeled, high-quality training, validation, and test data. As ML and deep learning models are increasingly integrated into production environments, it’s becoming more important than ever to have customizable, real-time data labeling pipelines that can continuously receive and process unlabeled data. For
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Shared by AWS Machine Learning November 3, 2020
Favorite Easier to share can mean harder to learn Image from wikimedia commons A common mistake companies often make when it comes to setting up knowledge sharing systems is to make it as easy as possible for people to share. I know that doesn’t sound like a mistake, but let
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Shared by Nick Milton November 2, 2020
Favorite Due to Indonesia’s vast size and population, timely and reliable access to healthcare can sometimes be a challenge. Halodoc aims to change that with a mobile first-telemedicine platform that connects Indonesians to doctors and helps them arrange appointments, medicine deliveries and tests. What’s distinctive about the Halodoc platform is
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Shared by Google AI Technology November 2, 2020
Favorite There have been breakthroughs in understanding COVID-19, such as how soon an exposed person will develop symptoms and how many people on average will contract the disease after contact with an exposed individual. The wider research community is actively working on accurately predicting the percent population who are exposed,
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Shared by AWS Machine Learning October 31, 2020
Favorite Every day there is something new going on in the world of AWS Machine Learning—from launches to new to use cases to interactive trainings. We’re packaging some of the not-to-miss information from the ML Blog and beyond for easy perusing each month. Check back at the end of each
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Shared by AWS Machine Learning October 31, 2020
Favorite Model training and serving steps are two essential pieces of a successful end-to-end machine learning (ML) pipeline. These two steps often require different software and hardware setups to provide the best mix for a production environment. Model training is optimized for a low-cost, feasible total run duration, scientific flexibility,
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Shared by AWS Machine Learning October 31, 2020
Favorite Based on our day to day experience, the information we consume is entirely digital. We read the news on our mobile devices far more than we do from printed copy newspapers. Tickets for sporting events, music concerts, and airline travel are stored in apps on our phones. One could
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Shared by AWS Machine Learning October 31, 2020
Favorite Conversational interfaces like chatbots have become an important channel for brands to communicate with their customers, partners, and employees. They offer faster service, 24/7 availability, and lower service costs. By analyzing your bot’s customer conversations, you can discover challenges in user experience, trending topics, and missed utterances. These additional
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Shared by AWS Machine Learning October 30, 2020
Favorite Many builders and teams on AWS use Confluence as a way of collaborating and sharing information within their teams and across their organizations. These types of workspaces are rich with data and contain sets of knowledge and information that can be a great source of truth to answer organizational
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Shared by AWS Machine Learning October 29, 2020
Favorite In a learning organisation we are all learners, but over time each individual moves towards being a teacher as well When an employee is very new to an organisation or to a topic, they are usually quite quiet in KM activities; in lesson capture meetings for example, or on
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Shared by Nick Milton October 29, 2020
Shared by AWS Machine Learning November 3, 2020
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