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Title: GitHub - PragyaCoder/DP100: Labs for Course DP-100: Designing and Implementing Data Science Solutions on Microsoft Azure · GitHub

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Description: Labs for Course DP-100: Designing and Implementing Data Science Solutions on Microsoft Azure - PragyaCoder/DP100

Open Graph Description: Labs for Course DP-100: Designing and Implementing Data Science Solutions on Microsoft Azure - PragyaCoder/DP100

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Opengraph URL: https://github.com/PragyaCoder/DP100

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01B - Intro to the Azure ML SDK.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/01B%20-%20Intro%20to%20the%20Azure%20ML%20SDK.ipynb
01B - Intro to the Azure ML SDK.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/01B%20-%20Intro%20to%20the%20Azure%20ML%20SDK.ipynb
02B - Using the Visual Designer.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/02B%20-%20Using%20the%20Visual%20Designer.ipynb
02B - Using the Visual Designer.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/02B%20-%20Using%20the%20Visual%20Designer.ipynb
03A - Running Experiments.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/03A%20-%20Running%20Experiments.ipynb
03A - Running Experiments.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/03A%20-%20Running%20Experiments.ipynb
03B - Training Models.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/03B%20-%20Training%20Models.ipynb
03B - Training Models.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/03B%20-%20Training%20Models.ipynb
04A - Working with Datastores.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/04A%20-%20Working%20with%20Datastores.ipynb
04A - Working with Datastores.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/04A%20-%20Working%20with%20Datastores.ipynb
04B - Working with Datasets.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/04B%20-%20Working%20with%20Datasets.ipynb
04B - Working with Datasets.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/04B%20-%20Working%20with%20Datasets.ipynb
05A - Working with Environments.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/05A%20-%20Working%20with%20Environments.ipynb
05A - Working with Environments.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/05A%20-%20Working%20with%20Environments.ipynb
05B - Working with Compute Targets.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/05B%20-%20Working%20with%20Compute%20Targets.ipynb
05B - Working with Compute Targets.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/05B%20-%20Working%20with%20Compute%20Targets.ipynb
06A - Creating a Pipeline.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/06A%20-%20Creating%20a%20Pipeline.ipynb
06A - Creating a Pipeline.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/06A%20-%20Creating%20a%20Pipeline.ipynb
06B - Publishing a Pipeline.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/06B%20-%20Publishing%20a%20Pipeline.ipynb
06B - Publishing a Pipeline.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/06B%20-%20Publishing%20a%20Pipeline.ipynb
07A - Creating a Real-time Inferencing Service.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/07A%20-%20Creating%20a%20Real-time%20Inferencing%20Service.ipynb
07A - Creating a Real-time Inferencing Service.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/07A%20-%20Creating%20a%20Real-time%20Inferencing%20Service.ipynb
07B - Creating a Batch Inferencing Service.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/07B%20-%20Creating%20a%20Batch%20Inferencing%20Service.ipynb
07B - Creating a Batch Inferencing Service.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/07B%20-%20Creating%20a%20Batch%20Inferencing%20Service.ipynb
08A - Tuning Hyperparameters.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/08A%20-%20Tuning%20Hyperparameters.ipynb
08A - Tuning Hyperparameters.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/08A%20-%20Tuning%20Hyperparameters.ipynb
08B - Using Automated Machine Learning.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/08B%20-%20Using%20Automated%20Machine%20Learning.ipynb
08B - Using Automated Machine Learning.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/08B%20-%20Using%20Automated%20Machine%20Learning.ipynb
09A - Reviewing Automated Machine Learning Explanations.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/09A%20-%20Reviewing%20Automated%20Machine%20Learning%20Explanations.ipynb
09A - Reviewing Automated Machine Learning Explanations.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/09A%20-%20Reviewing%20Automated%20Machine%20Learning%20Explanations.ipynb
09B - Interpreting Models.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/09B%20-%20Interpreting%20Models.ipynb
09B - Interpreting Models.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/09B%20-%20Interpreting%20Models.ipynb
10A - Monitoring a Model.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/10A%20-%20Monitoring%20a%20Model.ipynb
10A - Monitoring a Model.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/10A%20-%20Monitoring%20a%20Model.ipynb
10B - Monitoring Data Drift.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/10B%20-%20Monitoring%20Data%20Drift.ipynb
10B - Monitoring Data Drift.ipynbhttps://github.com/PragyaCoder/DP100/blob/master/10B%20-%20Monitoring%20Data%20Drift.ipynb
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