根据美国共享单车历史使用情况数据,建立神经网络模型,完整实现前向和反向传播,对模型进行训练使其具备预测未来单车使用量的能力,为共享单车公司的单车储备量提供决策支持。
在这一项目中,你将会从头开始构建一个神经网络,基于真实的数据集来进行预测!通过从零开始搭建神经网络,你将更好地理解梯度下降、反向传播等概念。这些都是我们以后接触更高级工具(如 Tensorflow)前必须掌握的重要概念。在这一项目中,你也将看到,如何运用这些网络来完成实际生活中的预测问题!
数据来自 UCI 机器学习数据库。
This project forked from shizhongli/bike_sharing_neural_network
本项目基于共享单车公司历史用户使用数据,创建神经网络模型,实现完整的前向和反向传播,训练模型使其具有预测未来单车使用量的能力,帮助共享单车公司决策单车的储备量以适配单车使用需求。
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