Simplify iterative machine learning model development by adding features to existing feature groups in Amazon SageMaker Feature Store

Favorite Feature engineering is one of the most challenging aspects of the machine learning (ML) lifecycle and a phase where the most amount of time is spent—data scientists and ML engineers spend 60–70% of their time on feature engineering. AWS introduced Amazon SageMaker Feature Store during AWS re:Invent 2020, which

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Shared by AWS Machine Learning August 2, 2022

The value of pull-based community meetings

Favorite Don’t just run your community meetings as presentations; instead engage in real multi-way dialogue around important questions. Brown bag lunch, by Gloria, on Flickr I have blogged several times about Push and Pull in Knowledge Management (aka Knowledge Supply and demand); about the dangers of focusing only on Push (such a

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Shared by Nick Milton August 1, 2022

Fine-tune and deploy a summarizer model using the Hugging Face Amazon SageMaker containers bringing your own script

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

Identify the location of anomalies using Amazon Lookout for Vision at the edge without using a GPU

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

Enhancing Backpropagation via Local Loss Optimization

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

What is an Open Source Program Office and why you should have one

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)