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End to End Data Science Project

Workflows--ML Pipeline

  1. Data Ingestion
  2. Data Validation
  3. Data Transformation-- Feature Engineering,Data Preprocessing
  4. Model Trainer
  5. Model Evaluation- MLFLOW,Dagshub

Workflows

  1. Update config.yaml
  2. Update schema.yaml
  3. Update params.yaml
  4. Update the entity
  5. Update the configuration manager in src config
  6. Update the components
  7. Update the pipeline
  8. Update the main.py =======

Datascienceproject

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End-to-end data science project covering EDA, feature engineering, model training, and evaluation

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