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brightsparc/README.md

Hello, Hola, Bonjour, As-Salaam-Alaikum, Niina Marni 👋

My name is Julian. I'm brightsparc on the internet 🌐. I'm currently based in Melbourne Australia 🇦🇺, working remotely on buliding a Generative AI stealth startup for talent teams. Previously I lead platform engineering remotely for Predibase, after 4 years at Amazon Web Serivces where as a Principal Solutions Architect I focused on helping customers on their MLOps journey. Prior to that I was applied data scientist building search and recommendations products.

Julian's GitHub stats

  • 🔭 I’m currently building a 🤖 Gen AI Startup.
  • 💬 Ask me about open roles we might have going.
  • 🌱 I’m interested in learning about the latest R&D in the ML infra 👨‍🔧
  • 👯 I’m contributin to open source ML projects.
  • ⚡ Fun fact: I enjoy running around after my 3 kids 👨‍👩‍👧‍👦 and my dog 🐶 milo.
  • 📫 How to reach me: Connect with me on Linkedin

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  1. aws-samples/amazon-sagemaker-safe-deployment-pipeline aws-samples/amazon-sagemaker-safe-deployment-pipeline Public

    Safe blue/green deployment of Amazon SageMaker endpoints using AWS CodePipeline, CodeBuild and CodeDeploy.

    Jupyter Notebook 104 240

  2. aws-samples/amazon-sagemaker-drift-detection aws-samples/amazon-sagemaker-drift-detection Public

    This sample demonstrates how to setup an Amazon SageMaker MLOps end-to-end pipeline for Drift detection

    Python 58 33

  3. aws-samples/amazon-sagemaker-ab-testing-pipeline aws-samples/amazon-sagemaker-ab-testing-pipeline Public

    Amazon SageMaker MLOps deployment pipeline for A/B Testing of machine learning models.

    Python 42 15