Application of Machine Learning in Agriculture

Part 1: Fundamentals of Smart Agriculture
1. Machine learning based Agriculture
2. Monitoring agriculture essentials
3. Livestock management in agriculture

Part 2: Market, Technology and products
4. Agriculture Economics
5. Digital Marketing and its impact
6. Technology and products

Part 3: Tools and Techniques
7. Modeling Techniques used in Smart Agriculture
8. Diseases detection
9. Food Security
10. Medicines Care Management
11. Detection and diagnosis of plant diseases
12. Machine Learning Technique for agriculture image recognition

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• Agricultura e lavoura
• Agricultura e indústrias relacionadas
• Aprendizagem mecânica

?AI; Agricultural digitalization; Agricultural marketing; Agricultural productivity; Agriculture; Agriculture production; Artificial intelligence; Artificial neural networks; Convolutional neural network; Crop; Crop diagnosis; Crop monitoring; Crop safety; Decision tree; Deep learning; Diseases detection; E-Mandi; E-value chain; Feature extraction; Forecasting; Full convolutional network (FCN); Fuzzy framework; Geospatial data; Image classification; Image mining; Image processing; Image recognition; Image segmentation; Internet of Things (IoT); Investment opportunities; Item splitting; ML in agriculture; Machine learning; Mobile agriculture; Mushroom disease; Pest detection; Plant diseases; Precision agriculture; Predictive analysis; Raspberry pi sensors; Regression; Remote monitoring; Robotics; Rubber stand age; Satellite images; Sentiment analysis; Smart agriculture; Stacked autoencoder; ThingSpeak; Tomato plant diseases; Transfer learning; U-net; Urban farmers; VGG-16; Virtual fencing; Weather prediction; YOLOv3; Yield prediction