1.4 KiB
1.4 KiB
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
- Open the notebook in Google Colab
- Run all cells — no installation needed
- Dataset auto-loads from raw GitHub URL
📊 Pipeline Steps
- Data Loading
- Exploratory Data Analysis
- One-Hot Encoding (Department, Attendance_Level, Favorite_Color)
- Random Forest Classification
- Model Evaluation
- Feature Importance Visualization
Part of Gyannetra's FDP workshop series