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A Model for Prediction of Tomato Crop Disease Using CNN

Real-world project · AICTE-aligned · AI-graded · Audit-ready certificate

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Milestones

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Core skills

About this project

A Model for Prediction of Tomato Crop Disease Using CNN

Milestones

2. Data collection (disease vs. healthy images)

5 marks 5d

3. Data preprocessing and augmentation

5 marks 5d

4. CNN architecture design

5 marks 5d

5. Training, testing, and hyperparameter tuning

5 marks 5d

6. Accuracy evaluation and confusion matrix

15 marks 5d

7. Deployment plan (mobile/web app optional)

15 marks 5d

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Skills you'll learn

Deep Learning (CNNs) Image Classification Python Programming Data Augmentation Model Evaluation (AccuracyConfusion Matrix)

Tools used

Python (TensorFlow/Keras or PyTorch) OpenCVNumPyMatplotlib Jupyter Notebooks or Google Colab PlantVillage or similar datasets

Prerequisites

Basics of Deep Learning and CNN architecture Python programming Understanding of image datasets and annotation

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You'll earn — Certificate (PDF)

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A Model for Prediction of Tomato Crop Disease Using CNN

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