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The system is trained on 10,000+ labeled agricultural images to predict crop conditions with high accuracy, and includes analytics and visualizations of model performance.\n\n---\n\n## 🧠 Core Features\n\n- 🤖 Trained 3 custom CNN architectures using **TensorFlow** and **Keras**\n- 📊 Achieved **90.07% accuracy** on validation data\n- 📈 Designed analytics scripts to evaluate 4 key model metrics:\n  - Accuracy\n  - Precision\n  - Recall\n  - Loss\n- 🌐 Visualized predictions using **Matplotlib** with bar graphs and cluster charts\n\n---\n\n## 🛠️ Tech Stack\n\n| Purpose                 | Technology         |\n|-------------------------|--------------------|\n| Model Training          | TensorFlow, Keras  |\n| Data Preprocessing      | Scikit-learn       |\n| Data Visualization      | Matplotlib         |\n| Language                | Python             |\n\n---\n\n## 🧪 Training Overview\n\n- Dataset: \u003e10,000 images across various crop-health categories  \n- Preprocessing: Normalization, augmentation, and one-hot encoding  \n- CNN Variants:\n  - ResNet-inspired shallow net\n  - Custom-built 6-layer CNN\n  - Lightweight MobileNetv2 baseline  \n- Evaluation: Accuracy calculated via validation split (90.07%)\n\n---\n\n## 📊 Visualizations\n\nUsing `matplotlib`, the following charts were generated:\n- **Bar graphs** comparing model performance\n- **Cluster plots** to group prediction categories\n- Accuracy/Loss trends over training epochs\n\n---\n\n## 📁 Files\n\n- `train_model.py` — Model architecture and training loop\n- `evaluate.py` — Script to calculate and compare model metrics\n- `visualize.py` — Generates performance graphs\n- `README.md` — Project documentation\n\n---\n\n## 🧠 Future Improvements\n\n- Integrate early stopping and learning rate schedulers\n- Expand dataset with underrepresented crops\n- Deploy trained model to a web/mobile interface for farmer use\n\n---\n\n## 📅 Timeline\n\n**January – February 2025**  \nCreated as a solo AI-agriculture capstone to explore the intersection of deep learning and food security.\n\n---\n\n## 📬 Contact\n\n**Kevin Chifamba**  \n📧 kevinnanashe@gmail.com  \n🔗 [LinkedIn](https://www.linkedin.com/in/yourprofile) • [GitHub](https://github.com/your-username)\n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpuureya2%2Fmachine-learning-tensorflow","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpuureya2%2Fmachine-learning-tensorflow","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpuureya2%2Fmachine-learning-tensorflow/lists"}