Favorite This is the second part of a series that showcases the machine learning (ML) lifecycle with a data mesh design pattern for a large enterprise with multiple lines of business (LOBs) and a Center of Excellence (CoE) for analytics and ML. In part 1, we addressed the data steward
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Shared by AWS Machine Learning July 30, 2022
Favorite Amazon SageMaker Studio is a web-based integrated development environment (IDE) for machine learning (ML) that lets you build, train, debug, deploy, and monitor your ML models. Each onboarded user in Studio has their own dedicated set of resources, such as compute instances, a home directory on an Amazon Elastic
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Shared by AWS Machine Learning July 30, 2022
Favorite There have been many recent advancements in the NLP domain. Pre-trained models and fully managed NLP services have democratised access and adoption of NLP. Amazon Comprehend is a fully managed service that can perform NLP tasks like custom entity recognition, topic modelling, sentiment analysis and more to extract insights from data
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Shared by AWS Machine Learning July 30, 2022
Favorite Automated defect detection using computer vision helps improve quality and lower the cost of inspection. Defect detection involves identifying the presence of a defect, classifying types of defects, and identifying where the defects are located. Many manufacturing processes require detection at a low latency, with limited compute resources, and
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Shared by AWS Machine Learning July 30, 2022
Favorite Customer satisfaction is a potent metric that directly influences the profitability of an organization. With rapid technological advances in the past decade or so, it’s even more important to elevate customer focus in the following ways: Making your organization accessible to your customers across multiple modalities, including voice, text,
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Shared by AWS Machine Learning July 30, 2022
Favorite Posted by Ehsan Amid, Research Scientist, and Rohan Anil, Principal Engineer, Google Research, Brain Team While model design and training data are key ingredients in a deep neural network’s (DNN’s) success, less-often discussed is the specific optimization method used for updating the model parameters (weights). Training DNNs involves minimizing
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Shared by Google AI Technology July 29, 2022
Favorite A well-designed Open Source Program Office is the center of competency for an organization’s Open Source operations and structure. The post What is an Open Source Program Office and why you should have one first appeared on Voices of Open Source. Click Here to View Original Source (opensource.org)
Favorite As enterprises move from running ad hoc machine learning (ML) models to using AI/ML to transform their business at scale, the adoption of ML Operations (MLOps) becomes inevitable. As shown in the following figure, the ML lifecycle begins with framing a business problem as an ML use case followed
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Shared by AWS Machine Learning July 28, 2022
Favorite Posted by Tuan Anh Nguyen, Staff Software Engineer, Google Assistant, and Sourish Chaudhuri, Staff Software Engineer, Google Research In natural conversations, we don’t say people’s names every time we speak to each other. Instead, we rely on contextual signaling mechanisms to initiate conversations, and eye contact is often all
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Shared by Google AI Technology July 27, 2022
Favorite Logistics and transportation companies track ETA (estimated time of arrival), which is a key metric for their business. Their downstream supply chain activities are planned based on this metric. However, delays often occur, and the ETA might differ from the product’s or shipment’s actual time of arrival (ATA), for
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Shared by AWS Machine Learning July 27, 2022