End to End Deep Learning Project Using MLOPS DVC Pipeline With Deployments Azure and AWS - Krish Naik

End to End Deep Learning Project Using MLOPS DVC Pipeline With Deployments Azure and AWS - Krish Naik

Krish Naik via YouTube Direct link

- Introduction

1 of 24

1 of 24

- Introduction

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End to End Deep Learning Project Using MLOPS DVC Pipeline With Deployments Azure and AWS - Krish Naik

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  1. 1 - Introduction
  2. 2 - Project Introduction
  3. 3 - Prerequisite
  4. 4 - Problem Statement Chicken Disease
  5. 5 - Project Demo
  6. 6 - Github Repository Setup
  7. 7 - Project Template Creation
  8. 8 - Requirements Installation & Project Setup
  9. 9 - Logging, Exception & Utils Modules
  10. 10 - Project Workflows
  11. 11 - Data Ingestion Notebook Experiment
  12. 12 - Data Ingestion Final Implementation
  13. 13 - Prepare Base Model Notebook Experiment
  14. 14 - Prepare Base Model Final Implementation
  15. 15 - Prepare Callbacks Notebook Experiment
  16. 16 - Prepare Callbacks Final Implementation
  17. 17 - Model Trainer Notebook Experiment
  18. 18 - Model Trainer Final Implementation
  19. 19 - Model Evaluation Notebook Experiment
  20. 20 - Model Evaluation Final Implementation
  21. 21 - Writing DVC file for tracking piplines
  22. 22 - Prediction Pipeline & User App
  23. 23 - Project CI/CD Deployment on AWS
  24. 24 - Project CI/CD Deployment on Azure

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