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Human Pose Estimation with Deep Learning – Ultimate Overview in 2024

Viso.ai

How pose estimation works: Deep learning methods Use Cases and pose estimation applications How to get started with AI motion analysis Real-time full body pose estimation in construction – built with Viso Suite About us: Viso.ai Get a demo for your organization. Definition: What is pose estimation? What Is Pose Estimation?

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How Sportradar used the Deep Java Library to build production-scale ML platforms for increased performance and efficiency

AWS Machine Learning Blog

The DJL is a deep learning framework built from the ground up to support users of Java and JVM languages like Scala, Kotlin, and Clojure. With the DJL, integrating this deep learning is simple. In our case, we chose to use a float[] as the input type and the built-in DJL classifications as the output type.

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Build ML features at scale with Amazon SageMaker Feature Store using data from Amazon Redshift

Flipboard

Deploy the CloudFormation template Complete the following steps to deploy the CloudFormation template: Save the CloudFormation template sm-redshift-demo-vpc-cfn-v1.yaml Enter a stack name, such as Demo-Redshift. You should see a new CloudFormation stack with the name Demo-Redshift being created. yaml locally.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

” – James Tu, Research Scientist at Waabi Play with this project live For more: Dive into documentation Get in touch if you’d like to go through a custom demo with your team Comet ML Comet ML is a cloud-based experiment tracking and optimization platform. SuperAnnotate SuperAnnotate specializes in image and video annotation tasks.

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Simplifying the Image Classification Workflow with Lightning & Comet ML

Heartbeat

Today, I’ll walk you through how to implement an end-to-end image classification project with Lightning , Comet ML, and Gradio libraries. First, we’ll build a deep-learning model with Lightning. PyTorch-Lightning As you know, PyTorch is a popular framework for building deep learning models.

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Batch Calibration for LLMs

Bugra Akyildiz

Check the separated audio examples in the Demo Page ! LLMs are powerful but expensive to run, and generating responses or code auto-completion can quickly accumulate costs, especially when serving many users. BC has been shown to outperform previous calibration methods on a variety of natural language and image classification tasks.

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Simplify Deployment and Monitoring of Foundation Models with DataRobot MLOps

DataRobot Blog

The creation of foundation models is one of the key developments in the field of large language models that is creating a lot of excitement and interest amongst data scientists and machine learning engineers. These models are trained on massive amounts of text data using deep learning algorithms. and its affiliates.

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