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
Crop Disease Detection with CNNs
Leaf-image classifier with an offline mobile front end
3 weeks build
Overview
A transfer-learning classifier trained on leaf imagery that identifies crop diseases from a phone photo, explains the prediction with a Grad-CAM heat map, and suggests treatment, working fully offline through an on-device TFLite model.
What makes it stand up
- 01Transfer learning with EfficientNet and strong augmentation
- 02Grad-CAM overlays that show what the model looked at
- 03Quantised TFLite model for offline phone inference
- 04Treatment advisory database with local-language strings
- 05Confusion matrix and per-class report for your write-up
Module breakdown
- 01
Dataset
Cleaning, splitting and augmentation pipeline.
- 02
Training
Fine-tuning schedule, callbacks and checkpointing.
- 03
Explainability
Grad-CAM heat maps rendered in-app.
- 04
Mobile app
Camera capture, offline inference and history.
- 05
Advisory
Disease-to-treatment mapping with severity notes.
After this, you will be able to
- Explain transfer learning versus training from scratch
- Defend your accuracy numbers with a proper test split
- Show offline inference on a real phone
Technology stack
- Python
- TensorFlow
- EfficientNet
- Flutter
- Flask
- TFLite
- Level
- Major Project
- Domain
- Machine Learning
- Build time
- 3 weeks
- Difficulty
- Rating
- 4.7 / 5 · 186
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