# kushalj123/kickstarter-prediction architecture

> Architecture diagram of the GitHub repository kushalj123/kickstarter-prediction, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-28). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/kushalj123/kickstarter-prediction
- Repository: https://github.com/kushalj123/kickstarter-prediction

## Overview

This is a Google Colab notebook project for predicting Kickstarter campaign success from pre-launch features. Its documented workflow reads April and May 2021 CSV collections from Google Drive, cleans and merges each month, engineers features, trains an XGBoost classifier, evaluates it, and saves predictions. The README supports these stage relationships, but no notebook source excerpts were available to verify finer-grained calls or implementation details; all repository components therefore point to the notebook path.

Main entry points: [`ML_miniproject_PES1UG23CS319_PES1UG23CS343.ipynb`](https://github.com/kushalj123/kickstarter-prediction/blob/main/ML_miniproject_PES1UG23CS319_PES1UG23CS343.ipynb) (Clean and merge)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_data_prep["Data preparation"]
  node_clean_merge["Clean and merge"]
  node_cleaned_data["Cleaned monthly data"]
  node_feature_engineering["Feature engineering"]
end

subgraph group_modeling["Modeling and evaluation"]
  node_xgboost["XGBoost training"]
  node_evaluation["Model evaluation"]
end

subgraph group_outputs["Saved outputs"]
  node_predictions["Prediction CSV"]
end

node_user(("Notebook user"))
node_drive["Google Drive"]
node_raw_data["Monthly CSVs"]

node_user -->|"runs notebook"| node_clean_merge
node_drive -->|"provides CSVs"| node_raw_data
node_clean_merge -->|"reads and cleans"| node_raw_data
node_clean_merge -->|"writes monthly data"| node_cleaned_data
node_cleaned_data -->|"provides data"| node_feature_engineering
node_feature_engineering -->|"provides features"| node_xgboost
node_xgboost -->|"evaluated by"| node_evaluation
node_xgboost -->|"saves predictions"| node_predictions
node_predictions -->|"stored in"| node_drive

click node_clean_merge "https://github.com/kushalj123/kickstarter-prediction/blob/main/ML_miniproject_PES1UG23CS319_PES1UG23CS343.ipynb"
click node_cleaned_data "https://github.com/kushalj123/kickstarter-prediction/blob/main/ML_miniproject_PES1UG23CS319_PES1UG23CS343.ipynb"
click node_feature_engineering "https://github.com/kushalj123/kickstarter-prediction/blob/main/ML_miniproject_PES1UG23CS319_PES1UG23CS343.ipynb"
click node_xgboost "https://github.com/kushalj123/kickstarter-prediction/blob/main/ML_miniproject_PES1UG23CS319_PES1UG23CS343.ipynb"
click node_evaluation "https://github.com/kushalj123/kickstarter-prediction/blob/main/ML_miniproject_PES1UG23CS319_PES1UG23CS343.ipynb"
click node_predictions "https://github.com/kushalj123/kickstarter-prediction/blob/main/ML_miniproject_PES1UG23CS319_PES1UG23CS343.ipynb"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_clean_merge,node_cleaned_data,node_feature_engineering,node_user toneBlue
class node_xgboost,node_evaluation toneAmber
class node_predictions toneMint
class node_drive,node_raw_data toneIndigo
```

## Components

### Data preparation

- [Clean and merge](https://github.com/kushalj123/kickstarter-prediction/blob/main/ML_miniproject_PES1UG23CS319_PES1UG23CS343.ipynb): `ML_miniproject_PES1UG23CS319_PES1UG23CS343.ipynb`
- [Cleaned monthly data](https://github.com/kushalj123/kickstarter-prediction/blob/main/ML_miniproject_PES1UG23CS319_PES1UG23CS343.ipynb): `ML_miniproject_PES1UG23CS319_PES1UG23CS343.ipynb`
- [Feature engineering](https://github.com/kushalj123/kickstarter-prediction/blob/main/ML_miniproject_PES1UG23CS319_PES1UG23CS343.ipynb): `ML_miniproject_PES1UG23CS319_PES1UG23CS343.ipynb`

### Modeling and evaluation

- [XGBoost training](https://github.com/kushalj123/kickstarter-prediction/blob/main/ML_miniproject_PES1UG23CS319_PES1UG23CS343.ipynb): `ML_miniproject_PES1UG23CS319_PES1UG23CS343.ipynb`
- [Model evaluation](https://github.com/kushalj123/kickstarter-prediction/blob/main/ML_miniproject_PES1UG23CS319_PES1UG23CS343.ipynb): `ML_miniproject_PES1UG23CS319_PES1UG23CS343.ipynb`

### Saved outputs

- [Prediction CSV](https://github.com/kushalj123/kickstarter-prediction/blob/main/ML_miniproject_PES1UG23CS319_PES1UG23CS343.ipynb): `ML_miniproject_PES1UG23CS319_PES1UG23CS343.ipynb`

### Other components

- **Notebook user**
- **Google Drive**
- **Monthly CSVs**

## Connections

- Notebook user → Clean and merge: runs notebook
- Google Drive → Monthly CSVs: provides CSVs
- Clean and merge → Monthly CSVs: reads and cleans
- Clean and merge → Cleaned monthly data: writes monthly data
- Cleaned monthly data → Feature engineering: provides data
- Feature engineering → XGBoost training: provides features
- XGBoost training → Model evaluation: evaluated by
- XGBoost training → Prediction CSV: saves predictions
- Prediction CSV → Google Drive: stored in