pytorch数据分类

A python-based machine learning framework, providing tensors, dynamic neural networks and strong GPU acceleration.

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Jupyter Notebook / 全中文注释.(The loss function of retinanet based on pytorch).(You can use it on one-stage detection task or classifical task, to solve data imbalance influence).用于one-stage目标检测算法,提升检测效果.你也可以在分类任务中使用该损失函数,解决数据不平衡问题.

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1. Tabular data 不同行间没有顺序，不同列可以是不同的数据类型。（PyTorch中的tensors是homogeneous列同质的，信息在PyTorch中以数字方式存储，典型的是浮点型也有整形。） wine 数据集：https://archive.ics.uci.edu/ml/mach

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一、pytorch 基础练习 主要学习了如何使用torch定义数据以及对数据的一些操作 示例代码中进行点积运算(m @ v)要求数据类型是float，因此前面v定义的时候需要指定dtype，如下所示， # Create tensor of numbers from 1 to 5# 注意这里结果是1到