https://github.com/xlegend1024/az-cloudscale-adv-analytics
Azure Hands-on Lab for Cloud Scale Adv. Analytics
https://github.com/xlegend1024/az-cloudscale-adv-analytics
adf azure azurekeyvault azuremlstudio databricks
Last synced: 10 months ago
JSON representation
Azure Hands-on Lab for Cloud Scale Adv. Analytics
- Host: GitHub
- URL: https://github.com/xlegend1024/az-cloudscale-adv-analytics
- Owner: xlegend1024
- Created: 2018-09-06T21:28:16.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2019-09-25T19:57:12.000Z (over 6 years ago)
- Last Synced: 2025-07-30T14:13:03.722Z (10 months ago)
- Topics: adf, azure, azurekeyvault, azuremlstudio, databricks
- Language: Jupyter Notebook
- Homepage:
- Size: 16.3 MB
- Stars: 7
- Watchers: 1
- Forks: 10
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Cloud Scale Advanced Analtyics
Experience end-to-end Advanced Analytics on cloud using Blob, ADF, Databricks, SQLDB and Azure Machine Leaning Studio.
In this hands on lab, you can understand how to apply following Azure services to your project
* Azure Data Factory
* Azure Databricks
* Azure SQL Database
* Azure Key Vault
After the workshop you will be able to:
1. Understand process and architecture for cloud scale andvanced analaytics project
1. Create appropreate Azure services for data prep. & training environment
1. Know how to wanggle data in a scale
1. Expermiments on data and select the best model
1. Deploy and interact with your score model
## Architecture
## Scenario
Extract data from a web and load the data to Azure Blob storage. Mount the Azure Blob storage to Azure Databricks to prepare the data for Machine Learning. When save prepared data on Azure Blob, access the prepared data from Azure Machine Learning Studio. Conduct machine learning experiments and select the best model for prediction. When a model is selected, deploy the score model as a web service from the Azure Machine Learning Studio. Lastly, extract new data set from SQL Database and
### [Lab 00. Create hands on lab environment](https://github.com/xlegend1024/az-cloudscale-adv-analytics/blob/master/00.SetupEnv.md)
1. Create Hands-on Lab envrironment using a script
### [Lab 01. Ingest](https://github.com/xlegend1024/az-cloudscale-adv-analytics/blob/master/01Ingest.md)
1. Create Azure Data Factory (v2)
1. Create Data Pipeline
### [Lab 02. Create Azure Databricks](https://github.com/xlegend1024/az-cloudscale-adv-analytics/blob/master/02DataWrangling.md)
1. Create Azure Databricks
1. Create Azure Databricks cluster
1. Import and Run Notebook
## Labs for __Data Scientist__
### [Lab 03. Data Wrangling and Training](https://github.com/xlegend1024/az-cloudscale-adv-analytics/blob/master/AzureDatabricks/06_MLlib_Classification_Training.ipynb)
Import following url from Azure Databricks
```
https://github.com/xlegend1024/az-adb-aml-lab/raw/master/databricks/az-adb-aml-lab.dbc
```
### [Lab 04. Run Notebook within ADF Pipeline](https://github.com/xlegend1024/az-cloudscale-adv-analytics/blob/master/AzureDataFactory/adf_adb_prediction.md)
Use Azure Data Factory for batch scoring
### [Lab 05. Operationalize score model using Azure Machine Leaerning](https://github.com/xlegend1024/az-cloudscale-adv-analytics/blob/master/AzureDatabricks/07_MLlib_Classification_Deployment.ipynb)
Import following url from Azure Databricks
```
https://github.com/xlegend1024/az-cloudscale-adv-analytics/blob/master/AzureDatabricks/07_MLlib_Classification_Deployment.ipynb
```
### Lab 06. Azure AutoML
Import following url from Azure Databricks
```
https://github.com/xlegend1024/az-adb-aml-lab/raw/master/databricks/az-adb-aml-lab.dbc
```
## [Labs for __Citizenship Data Scientist__](https://github.com/xlegend1024/az-cloudscale-adv-analytics/blob/master/README_DE.md)
---
[Start Lab > 01. Ingest Data](https://github.com/xlegend1024/az-cloudscale-adv-analytics/blob/master/00.SetupEnv.md)
---
## Sources and references
* https://docs.microsoft.com/en-us/azure/machine-learning/studio/azure-ml-customer-churn-scenario
* https://github.com/Azure/MachineLearningSamples-ChurnPrediction
* https://github.com/jakazmie/ADBLabs