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Title: GitHub - SQLShark/MachineLearningFromModelToProduction: This repo holds all the content for the Machine Learning training day

Open Graph Title: GitHub - SQLShark/MachineLearningFromModelToProduction: This repo holds all the content for the Machine Learning training day

X Title: GitHub - SQLShark/MachineLearningFromModelToProduction: This repo holds all the content for the Machine Learning training day

Description: This repo holds all the content for the Machine Learning training day - SQLShark/MachineLearningFromModelToProduction

Open Graph Description: This repo holds all the content for the Machine Learning training day - SQLShark/MachineLearningFromModelToProduction

X Description: This repo holds all the content for the Machine Learning training day - SQLShark/MachineLearningFromModelToProduction

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tpm@adatis.co.uk

Opengraph URL: https://github.com/SQLShark/MachineLearningFromModelToProduction

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https://github.com/SQLShark/MachineLearningFromModelToProduction/blob/master/Images/Header1.png
https://github.com/SQLShark/MachineLearningFromModelToProduction#machine-learning-from-model-to-production-using-the-cloud-containers-and-devops
https://github.com/SQLShark/MachineLearningFromModelToProduction#devops-for-machine-learning-blog-series
Terry McCann - DevOps for Data Sciencehttp://www.hyperbi.co.uk/applying-devops-to-data-science/
https://github.com/SQLShark/MachineLearningFromModelToProduction#todays-abstract
https://github.com/SQLShark/MachineLearningFromModelToProduction#agenda
M0 - Title Intro Agenda https://github.com/SQLShark/MachineLearningFromModelToProduction/blob/master/Slides/M0%20-%20Introduction.pdf
Lab 0 - Check everyone is set up https://github.com/SQLShark/MachineLearningFromModelToProduction/tree/master/Labs/Lab%2000
M1 - Intro to Machine Learning with Python https://github.com/SQLShark/MachineLearningFromModelToProduction/blob/master/Slides/M1%20-%20An%20Introduction%20to%20Machine%20Learning%20with%20Python.pdf
Python Fundamentalshttps://github.com/SQLShark/MachineLearningFromModelToProduction/blob/master/Notebooks/001%20-%20Python%20Fundamentals.ipynb
Demo - Clustering https://github.com/SQLShark/MachineLearningFromModelToProduction/blob/master/Notebooks/002%20-%20Python%20K-Means.ipynb
Demo - Regression https://github.com/SQLShark/MachineLearningFromModelToProduction/blob/master/Notebooks/003%20-%20Python%20Regression.ipynb
Demo - Classification https://github.com/SQLShark/MachineLearningFromModelToProduction/blob/master/Notebooks/004%20-%20Python%20Classification%20.ipynb
M2 - Creating our first Machine learning model.https://github.com/SQLShark/MachineLearningFromModelToProduction/blob/master/Slides/M2%20-%20Creating%20your%20first%20Machine%20Learning%20model.pdf
Demo - Creating a model - Diabetes Regressionhttps://github.com/SQLShark/MachineLearningFromModelToProduction/blob/master/Notebooks/200%20-%20ExploringTheDiabetesData.ipynb
Lab 1 - Creating a Python Modelhttps://github.com/SQLShark/MachineLearningFromModelToProduction/tree/master/Labs/Lab%2001
M3 - Python Serailisation.https://github.com/SQLShark/MachineLearningFromModelToProduction/blob/master/Slides/M2%20-%20Creating%20your%20first%20Machine%20Learning%20model.pdf
Demo - Serialisation in Python - Picklehttps://github.com/SQLShark/MachineLearningFromModelToProduction/blob/master/Notebooks/100%20-%20PickleExample.ipynb
Lab 2 - The basics of serialisation in Pythonhttps://github.com/SQLShark/MachineLearningFromModelToProduction/tree/master/Labs/Lab%2002
M4 - Creating REST APIshttps://github.com/SQLShark/MachineLearningFromModelToProduction/blob/master/Slides/M4%20-%20Creating%20a%20REST%20API.pdf
Lab 3 - Adding Flask to our model to expose an APIhttps://github.com/SQLShark/MachineLearningFromModelToProduction/tree/master/Labs/Lab%2003
M5 - An introduction to Dockerhttps://github.com/SQLShark/MachineLearningFromModelToProduction/blob/master/Slides/M5%20-%20An%20Introduction%20to%20Docker.pdf
Lab 4 - Hello World! in Dockerhttps://github.com/SQLShark/MachineLearningFromModelToProduction/tree/master/Labs/Lab%2004
Lab 5 - Deploying a web app in to Dockerhttps://github.com/SQLShark/MachineLearningFromModelToProduction/tree/master/Labs/Lab%2005
Lab 6 - Deploying our model in to Dockerhttps://github.com/SQLShark/MachineLearningFromModelToProduction/tree/master/Labs/Lab%2006
M6 - An Introduction to Kuberneteshttps://github.com/SQLShark/MachineLearningFromModelToProduction/blob/master/Slides/M6%20-%20An%20Introduction%20to%20Kubernetes.pdf
Lab 7 - Deploying Azure Container Reghttps://github.com/SQLShark/MachineLearningFromModelToProduction/tree/master/Labs/Lab%2007
Lab 8 - Deploying our model in Kuberneteshttps://github.com/SQLShark/MachineLearningFromModelToProduction/tree/master/Labs/Lab%2008
M7 - DevOps for Machine Learninghttps://github.com/SQLShark/MachineLearningFromModelToProduction/blob/master/Slides/M7%20-%20DevOps%20for%20Machine%20Learning.pdf
Demo - Setting up a Build pipeline for deploying changeshttps://github.com/SQLShark/MachineLearningFromModelToProduction/blob/master
M8 - Extending the design - The Rendezvous patternhttps://github.com/SQLShark/MachineLearningFromModelToProduction/blob/master/Slides/M8%20-%20ManagingMultipleModelsInProduction.pdf
https://github.com/SQLShark/MachineLearningFromModelToProduction#labs
Lab 1 - Creating a Python Modelhttps://github.com/SQLShark/MachineLearningFromModelToProduction/tree/master/Labs/Lab%2001
Lab 2 - The basics of serialisation in Pythonhttps://github.com/SQLShark/MachineLearningFromModelToProduction/tree/master/Labs/Lab%2002
Lab 3 - Adding Flask to our model to expose an APIhttps://github.com/SQLShark/MachineLearningFromModelToProduction/tree/master/Labs/Lab%2003
Lab 4 - Hello World! in Dockerhttps://github.com/SQLShark/MachineLearningFromModelToProduction/tree/master/Labs/Lab%2004
Lab 5 - Deploying a web app in to Dockerhttps://github.com/SQLShark/MachineLearningFromModelToProduction/tree/master/Labs/Lab%2005
Lab 6 - Deploying our model in to Dockerhttps://github.com/SQLShark/MachineLearningFromModelToProduction/tree/master/Labs/Lab%2006
Lab 7 - Deploying Azure Container Reghttps://github.com/SQLShark/MachineLearningFromModelToProduction/tree/master/Labs/Lab%2007
Lab 8 - Deploying our model in Kuberneteshttps://github.com/SQLShark/MachineLearningFromModelToProduction/tree/master/Labs/Lab%2008
https://github.com/SQLShark/MachineLearningFromModelToProduction#structure-of-github
herehttps://github.com/Adatis/ModernDataWarehouseWorkshop/tree/master/Slides
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https://azure.microsoft.com/en-gb/offers/ms-azr-0044p/https://azure.microsoft.com/en-gb/offers/ms-azr-0044p/
https://www.docker.com/https://www.docker.com/
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https://github.com/SQLShark/MachineLearningFromModelToProduction#about-the-speakers
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@SQLSharkhttps://twitter.com/SQLShark
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http://clipper.aihttp://clipper.ai
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