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添加 Pytorch版本的cnn + 更新 猫狗识别的描述 #121

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Merged
jiangzhonglian merged 3 commits into from
Mar 31, 2018
Merged

添加 Pytorch版本的cnn + 更新 猫狗识别的描述 #121

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a1b0d6f
添加 Pytorch版本的cnn
jiangzhonglian Mar 27, 2018
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删除重复地方
jiangzhonglian Mar 28, 2018
ec6bf06
更新 猫狗识别的描述
jiangzhonglian Mar 31, 2018
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删除重复地方
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@jiangzhonglian
jiangzhonglian committed Mar 28, 2018
commit 5b29ba13bc0b8c07685bb3d00618fda8cc7fabb3
23 changes: 0 additions & 23 deletions competitions/getting-started/house-price/README.md
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Expand Up @@ -56,29 +56,6 @@ import matplotlib.pyplot as plt

### 特征说明


## 步骤:

一. 数据分析
1. 下载并加载数据
2. 总体预览:了解每列数据的含义,数据的格式等
3. 数据初步分析,使用统计学与绘图:初步了解数据之间的相关性,为构造特征工程以及模型建立做准备

二. 特征工程
1. 根据业务,常识,以及第二步的数据分析构造特征工程.
2. 将特征转换为模型可以辨别的类型(如处理缺失值,处理文本进行等)

三. 模型选择
1. 根据目标函数确定学习类型,是无监督学习还是监督学习,是分类问题还是回归问题等.
2. 比较各个模型的分数,然后取效果较好的模型作为基础模型.

四. 模型融合

五. 修改特征和模型参数
1. 可以通过添加或者修改特征,提高模型的上限.
2. 通过修改模型的参数,是模型逼近上限


## 一. 数据分析

### 数据下载和加载
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