anuragsingz/diamond-price-prediction-main

How anuragsingz/diamond-price-prediction-main works

This repository is a diamond-price regression application with a Flask prediction interface and a separate model-training workflow. A user submits diamond attributes through the form; the app converts them to a dataframe, loads saved preprocessing and model artifacts, predicts a price, and renders the result. Training ingests and splits gemstone data, transforms features, trains candidate regressors, and evaluates the model with MLflow tracking. The source shows these component calls, but there are artifact path/name inconsistencies, so the graph does not assume training artifacts successfully feed evaluation or inference. The MLflow capability is also documented in the README; unsampled integrations are not inferred.

Main entry points: Model_trainer.py Model trainer · app.py Flask routes · Data_transformation.py Feature transformation · Prediction_Pipeline.py Prediction pipeline

Components 17

Prediction web app

Flask routes app.py
Input form templates/form.html
Price result templates/result.html
Input dataframe src/DiamondPricePrediction/pipelines/Prediction_Pipeline.py
Prediction pipeline src/DiamondPricePrediction/pipelines/Prediction_Pipeline.py

Model training

Data ingestion src/DiamondPricePrediction/components/Data_ingestion.py
Gemstone dataset Notebook_Experiments/Data/gemstone.csv
Train/test CSVs Artifacts
Feature transformation src/DiamondPricePrediction/components/Data_transformation.py
Model trainer src/DiamondPricePrediction/components/Model_trainer.py
Model evaluation src/DiamondPricePrediction/components/Model_evaluation.py

Model artifacts

Model artifacts Artifacts

Shared internals

Serialization and scoring src/DiamondPricePrediction/utils/utils.py
Application logging src/DiamondPricePrediction/logger.py
Custom exceptions src/DiamondPricePrediction/exception.py

Other components

Browser user
MLflow tracking

Connections 25

Browser user → Flask routes: submits attributes app.py
Flask routes → Input form: renders form app.py
Flask routes → Input dataframe: creates input app.py
Input dataframe → Prediction pipeline: provides dataframe app.py
Flask routes → Prediction pipeline: requests prediction app.py
Flask routes → Price result: renders price app.py
Browser user → Price result: views result
Data ingestion → Gemstone dataset: reads dataset src/DiamondPricePrediction/components/Data_ingestion.py
Data ingestion → Train/test CSVs: writes splits src/DiamondPricePrediction/components/Data_ingestion.py
Data ingestion → Feature transformation: returns split paths src/DiamondPricePrediction/pipelines/Training_pipeline.py
Feature transformation → Train/test CSVs: reads splits src/DiamondPricePrediction/components/Data_transformation.py
Feature transformation → Serialization and scoring: saves preprocessor src/DiamondPricePrediction/components/Data_transformation.py
Feature transformation → Model trainer: provides arrays src/DiamondPricePrediction/pipelines/Training_pipeline.py
Model trainer → Serialization and scoring: evaluates candidates src/DiamondPricePrediction/components/Model_trainer.py
Model trainer → Serialization and scoring: saves selected model src/DiamondPricePrediction/components/Model_trainer.py
Model trainer → Model artifacts: writes model src/DiamondPricePrediction/components/Model_trainer.py
Model trainer → Model evaluation: starts evaluation src/DiamondPricePrediction/pipelines/Training_pipeline.py
Model evaluation → Serialization and scoring: loads model src/DiamondPricePrediction/components/Model_evaluation.py
Model evaluation → MLflow tracking: logs metrics and model src/DiamondPricePrediction/components/Model_evaluation.py
Prediction pipeline → Serialization and scoring: loads artifacts src/DiamondPricePrediction/pipelines/Prediction_Pipeline.py
Prediction pipeline → Model artifacts: reads model and preprocessor src/DiamondPricePrediction/pipelines/Prediction_Pipeline.py
Data ingestion → Application logging: logs progress src/DiamondPricePrediction/components/Data_ingestion.py
Feature transformation → Custom exceptions: raises errors src/DiamondPricePrediction/components/Data_transformation.py
Model trainer → Custom exceptions: raises errors src/DiamondPricePrediction/components/Model_trainer.py
Prediction pipeline → Custom exceptions: raises errors src/DiamondPricePrediction/pipelines/Prediction_Pipeline.py

Drawn by GitDiagram on November 14, 2026 from the repository's file tree, README and source files. Read as Markdown ·