39 lines
1.4 KiB
Markdown
39 lines
1.4 KiB
Markdown
# FDP - Data Science Pipeline: End-to-End Workflow
|
||
|
||
**Topic:** Data Science Pipeline | **Host:** Jodhpur Institute of Engineering & Technology (JIET)
|
||
|
||
## 📂 Contents
|
||
|
||
| File | Description |
|
||
|------|-------------|
|
||
| `fdp-colab-content/student_stress_data.csv` | Synthetic dataset of 300 student records for stress level prediction |
|
||
| `fdp-colab-content/FDP_Student_Stress_Prediction.ipynb` | Google Colab notebook — zero setup required |
|
||
| `fdp-colab-content/FDP_PreRead_StudentStress.pdf` | Pre-read material for FDP attendees |
|
||
| `fdp-colab-content/generate_dataset.py` | Dataset generator script |
|
||
| `fdp-colab-content/pre_read.html` | Pre-read material source (HTML) |
|
||
|
||
## 🎯 Dataset Overview
|
||
|
||
**300 student records × 8 columns**
|
||
- **Target:** `Stress_Level` (0 = Not Stressed, 1 = Stressed)
|
||
- **Features:** Department, Attendance_Level, Favorite_Color, Weekly_Study_Hours, Assignment_Submission_Pct, Backlogs_Count
|
||
|
||
## 🚀 Using the Colab Notebook
|
||
|
||
1. Open the notebook in [Google Colab](https://colab.research.google.com/)
|
||
2. Run all cells — no installation needed
|
||
3. Dataset auto-loads from raw GitHub URL
|
||
|
||
## 📊 Pipeline Steps
|
||
|
||
1. Data Loading
|
||
2. Exploratory Data Analysis
|
||
3. One-Hot Encoding (Department, Attendance_Level, Favorite_Color)
|
||
4. Random Forest Classification
|
||
5. Model Evaluation
|
||
6. Feature Importance Visualization
|
||
|
||
---
|
||
|
||
*Part of Gyannetra's FDP workshop series*
|