This repository shows the following
☑️ IPL Best Batsman using 6 different metrics and an unsupervised learning algorithm Principal Component Analysis for each of the seasons from 2007 to 2021
☑️ IPL Best Bowler using 4 different metrics and an unsupervised learning algorithm Principal Component Analysis for each of the seasons from 2007 to 2021
☑️ Create a Streamlit UI on top of the logic
☑️ Create a Container Image and run it on local Docker
☑️ Deploy the Container Image in Azure Container Instances
☑️ Deploy the Container Image in Azure Kubernetes Cluster
☑️ Deploy the Container Image in Azure Container Apps
Cricket Analytics Playlist
This has videos on the calculation of the IPL best batsman and best bowler. This also has the details and inner workings of the PCA used in the analysis.
| FileName | Description |
|---|---|
| Dockerfile | Docker file to produce a container image |
| requirements.txt | The libraries required for the Dockerfile are present in the requirements.txt. The Dockerfile uses the requirements.txt |
| Docker_steps.md | The steps required to deploy the container in the local Docker Desktop |
| azure_aci_steps.md | Steps to deploy in Azure Container Instance |
| service_principal_aks_steps.md | Steps to deploy in Azure Kubernetes Service |
| azure_container_apps.md | Steps to deploy in Azure Container Apps |
| ALL_2021_IPL_MATCHES_BALL_BY_BALL.csv | IPL Ball by Ball data - 2021 |
| all_matches_details.csv | IPL Ball by Ball data for seasons 2007 to 2021 |
| analysis-bowler-pca-details.ipynb | This has the details of the IPython notebook for the PCA implementation |
Anomaly Detection in Resource Constrained Environments With Streaming Data