Create README.md

README.md

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+---
+tags:
+- time-series
+- agriculture
+- forecasting
+- tabular
+---
+
+# crop_yield_prediction_transformer
+
+## Overview
+A specialized Time-Series Transformer model built to predict agricultural crop yields based on historical growth patterns, soil moisture sensors, and meteorological forecasts. It outputs a probabilistic distribution of expected yield (tonnes/hectare) for the upcoming harvest cycle.
+
+## Model Architecture
+The architecture is based on a standard Encoder-Decoder Time-Series Transformer.
+
+
+
+- **Input Embedding:** Maps multi-variate features (temperature, rainfall, soil pH, nitrogen levels) into a dense vector space.
+- **Positional Encoding:** Injected to maintain the temporal order of growing seasons.
+- **Decoder:** Generates a 15-day prediction horizon based on a 30-day context window of environmental data.
+
+## Intended Use
+- **Precision Agriculture:** Helping farmers optimize fertilizer and water usage.
+- **Food Security:** Enabling governments to forecast domestic food production levels.
+- **Crop Insurance:** Providing data-driven risk assessment for insurance payouts based on climatic anomalies.
+
+## Limitations
+- **Extreme Weather Events:** Black swan events like sudden locust swarms or unprecedented floods are not captured by historical patterns.
+- **Local Specificity:** A model trained on European wheat data will not generalize to tropical rice paddies without extensive fine-tuning.
+- **Static Features:** Assumes consistent farming practices; sudden changes in technology or equipment are not modeled.