Crop Yield Prediction Dataset

# Context
The science of training machines to learn and produce models for future predictions is widely used, and not for nothing. Agriculture plays a critical role in the global economy. With the continuing expansion of the human population understanding worldwide crop yield is central to addressing food security challenges and reducing the impacts of climate change.

Crop yield prediction is an important agricultural problem. The Agricultural yield primarily depends on weather conditions (rain, temperature, etc), pesticides and accurate information about history of crop yield is an important thing for making decisions related to agricultural risk management and future predictions.

# Acknowledgements
All dataset(publicly available dataset) here are taken form FAO (Food and Agriculture Organization) and World Data Bank.
http://www.fao.org/home/en/
https://data.worldbank.org/

训练机器以学习和生成用于未来预测的模型的科学被广泛运用，实非徒然。农业在全球经济中扮演着至关重要的角色。随着人类人口的持续增长，理解全球作物产量对于应对粮食安全挑战以及减轻气候变化的影响至关重要。
作物产量预测是农业领域的一个关键问题。农业产量主要依赖于天气条件（如降雨、温度等）、农药以及关于作物产量历史的准确信息，这些对于农业风险管理及未来预测的相关决策至关重要。

致谢
本数据集（公开可获得的数据集）均来源于联合国粮食及农业组织（FAO）和世界银行数据库。
http://www.fao.org/home/en/
https://data.worldbank.org/

搜集汇总

背景与挑战

背景概述

该数据集包含全球10种主要作物的产量预测相关数据，涵盖农药使用、降雨量和平均温度等关键因素，时间跨度为1990年至2016年，数据来源于FAO和世界银行。适用于农业风险管理和机器学习预测模型的研究。