AI/ML
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How to Develop and Deploy a Customer Churn Prediction Model Using Python, Streamlit, and Docker
Customer churn is challenging, but we can combat it! Learn how Python, Streamlit, and Docker help you build a predictive model to minimize churn.
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Build and Deploy a Retail Store Items Detection System Using No-Code AI Vision at the Edge
In this tutorial, you’ll learn how to build a retail store items detection system using Docker and Node-RED, a low-code programming language for event-driven applications.
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How to Train and Deploy a Linear Regression Model Using PyTorch
Get an introduction to PyTorch, then learn how to use it for a simple problem like linear regression — and a simple way to containerize your application.
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How to Deploy GPU-Accelerated Applications on Amazon ECS with Docker Compose
Many applications can take advantage of GPU acceleration, in particular resource intensive Machine Learning (ML) applications. The development time of such applications may vary based on the hardware of the machine we use for development. Containerization will facilitate development due to reproducibility, and will make the setup easily transferable to other machines. Most importantly, a containerized application is easily deployable to platforms such as Amazon ECS, where it can take advantage of different hardware configurations.
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Top Developer Trends for 2021
What are the key trends relevant to development teams in 2021? Here the top picks from the Docker team.
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Depend on Docker for Kubeflow
In this blog, Docker Captain Alex Iankoulski shows you how to use Docker Desktop for Mac or Windows to run Kubeflow natively.
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