End to End Machine Learning Project Implementation with Dockers, GitHub Actions and Deployment

End to End Machine Learning Project Implementation with Dockers, GitHub Actions and Deployment

Krish Naik via YouTube Direct link

Running An Testing our application

13 of 17

13 of 17

Running An Testing our application

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End to End Machine Learning Project Implementation with Dockers, GitHub Actions and Deployment

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  1. 1 Understanding the dataset
  2. 2 Preparing Dataset And Basic Analysis
  3. 3 Preparing Dataset For Model Training
  4. 4 Training The Model
  5. 5 Performance Metrics
  6. 6 Prediction Of New Data
  7. 7 Pickling the model file
  8. 8 Setting Up Github And VS Code
  9. 9 Tools And Software Required
  10. 10 Creating A New Environment
  11. 11 Setting up Git
  12. 12 Creating A FLASK Web Application
  13. 13 Running An Testing our application
  14. 14 Prediction From Front End Application
  15. 15 Procfile for Heroku Deployment
  16. 16 Deploying The App To Heroku
  17. 17 Deploying The App Using Dockers

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