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Plug & Play Deployments of Machine Learning Models Using TensorFlow Serving

Plug & Play Deployments of Machine Learning Models Using TensorFlow Serving

  • Post author:Dennis Eilers
  • Post published:April 17, 2021
  • Post category:Dev Ops/Tooling
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Introduction In previous posts we have already explored several ways to bring your machine learning models into production (serverless with Algorithmia, or using FastAPI). Each approach has its advantages and…

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How to Make your Machine Learning Model Accessible as an API
Make Machine Learning Models Accessible as an API

How to Make your Machine Learning Model Accessible as an API

  • Post author:Dennis Eilers
  • Post published:April 2, 2021
  • Post category:Dev Ops/Tooling
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Motivation Finally! You have gathered all your data, cleaned and preprocessed it, fitted a model and the results on the test data fulfill the requirements... Now what? Depending on your…

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How to Train a Machine Learning Model – The DevOps Way

How to Train a Machine Learning Model – The DevOps Way

  • Post author:Dennis Eilers
  • Post published:March 6, 2021
  • Post category:Dev Ops/Tooling
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Motivation If you work as software engineer you most likely use version control systems for your code like git, commit to different branches of your project for different features and…

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DevOps for Data Science – How to Operationalize Ideas to Create Real Value

DevOps for Data Science – How to Operationalize Ideas to Create Real Value

  • Post author:Dennis Eilers
  • Post published:February 6, 2021
  • Post category:Dev Ops
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tl;dr: This series provides a comprehensive overview of how to operationalize your work as a data scientist. The structure is based on different scenarios to provide you a guide according…

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