PopularMajor Project
Machine Learning
AI Resume Screening System
NLP pipeline that ranks candidates against a job description
- Python
- spaCy
- scikit-learn
- FastAPI
- +2
₹4,499₹7,999
4.9/214 reviews
Machine Learning · Major Project
Disease Prediction System
Risk scoring from clinical data, with explainable outputs
3 weeks build
Overview
Predicts risk for several conditions from routine clinical measurements, and — the part that earns marks — explains every prediction with SHAP so a clinician can see which factors drove the score. Includes the calibration work most student projects skip entirely.
What makes it stand up
- 01SHAP explanations on every individual prediction
- 02Probability calibration, so a 70% score means 70%
- 03Class-imbalance handling done properly, not by oversampling blindly
- 04Several conditions from one shared pipeline
- 05A clear statement that this is decision support, never diagnosis
Module breakdown
- 01
Data
Cleaning, missing values and imbalance handling.
- 02
Models
Baselines through to gradient boosting.
- 03
Calibration
Reliability curves and probability correction.
- 04
Explainability
SHAP values, global and per-patient.
- 05
Interface
Input form, risk score and factor breakdown.
After this, you will be able to
- Explain why accuracy is the wrong metric on imbalanced clinical data
- Read a SHAP plot aloud for one patient
- State the ethical limits of the system without being prompted
Technology stack
- Python
- scikit-learn
- XGBoost
- SHAP
- Flask
- React
- Level
- Major Project
- Domain
- Machine Learning
- Build time
- 3 weeks
- Difficulty
- Rating
- 4.7 / 5 · 168
You receive
- Complete, commented source code
- 60-90 page project report (IEEE format)
- Editable presentation deck
- Architecture, ER and UML diagrams
- Local setup and deployment guide
- Sample dataset or seed data
- Viva question bank with answers
- One 45-minute walkthrough call
- 30 days of doubt-clearing support