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Favorite Be our guest as we celebrate 20 years of AI/ML innovation on October 25, 2022, 9:00 AM – 10:30 AM PT. The first 1,500 people to register will receive $50 of AWS credits. Register here. Over the past 20 years, Amazon has delivered many world firsts for artificial intelligence
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Shared by AWS Machine Learning October 1, 2022
Favorite This post is co-authored by Salma Taoufiq and Harini Kannan from Sophos. As a leader in next-generation cybersecurity, Sophos strives to protect more than 500,000 organizations and millions of customers across over 150 countries against evolving threats. Powered by threat intelligence, machine learning (ML), and artificial intelligence from Sophos
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Favorite Depending on the quality and complexity of data, data scientists spend between 45–80% of their time on data preparation tasks. This implies that data preparation and cleansing take valuable time away from real data science work. After a machine learning (ML) model is trained with prepared data and readied
Read More Shared by AWS Machine Learning September 30, 2022
Favorite Ten years from now, the technological fitness of clubs will be a key contributor towards their success. Today we’re already witnessing the potential of technology to revolutionize the understanding of football. xGoals quantifies and allows comparison of goal scoring potential of any shooting situation, while xThreat and EPV models
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Favorite Pressing or pressure in football is a process in which a team seeks to apply stress to the opponent player who possesses the ball. A team applies pressure to limit the time an opposition player has left to make a decision, reduce passing options, and ultimately attempt to turn
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Favorite GitHub is sponsoring Open Source Initiative’s Deep Dive: AI because we think it’s important for the community to unpack how open source software, process, and principles can help best deliver on the promise of AI. The post OSI’s Deep Dive is an essential discussion on the future of AI
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Shared by voicesofopensource September 29, 2022
Favorite Data scientists often train their models locally and look for a proper hosting service to deploy their models. Unfortunately, there’s no one set mechanism or guide to deploying pre-trained models to the cloud. In this post, we look at deploying trained models to Amazon SageMaker hosting to reduce your
Read More Shared by AWS Machine Learning September 28, 2022
Favorite Amazon SageMaker Pipelines allows data scientists and machine learning (ML) engineers to automate training workflows, which helps you create a repeatable process to orchestrate model development steps for rapid experimentation and model retraining. You can automate the entire model build workflow, including data preparation, feature engineering, model training, model
Read More Shared by AWS Machine Learning September 28, 2022
Favorite The proliferation of machine learning (ML) across a wide range of use cases is becoming prevalent in every industry. However, this outpaces the increase in the number of ML practitioners who have traditionally been responsible for implementing these technical solutions to realize business outcomes. In today’s enterprise, there is
Read More Shared by AWS Machine Learning September 28, 2022
Favorite Amazon Kendra is a highly accurate and simple-to-use intelligent search service powered by machine learning (ML). Amazon Kendra offers a suite of data source connectors to simplify the process of ingesting and indexing your content, wherever it resides. Valuable data in organizations is stored in both structured and unstructured
Read More Shared by AWS Machine Learning September 28, 2022