update

competitions/getting-started/house-price.md

@@ -1,16 +1,16 @@
-##**房价预测**
+## **房价预测**
 
 ***
 
 [房价预测](https://www.kaggle.com/c/house-prices-advanced-regression-techniques):Predict sales prices and practice feature engineering
 
-###**内容说明**
+### **内容说明**
 
 - Ask a home buyer to describe their dream house, and they probably won't begin with the height of the basement ceiling or the proximity to an east-west railroad. But this playground competition's dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence.
 
 - With 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa, this competition challenges you to predict the final price of each home.
 
-###**开发流程**
+### **开发流程**
 
 >收集数据:[数据集](https://www.kaggle.com/c/house-prices-advanced-regression-techniques/data)
 
@@ -28,12 +28,14 @@ def dataProcess(df_train, df_test):
 ```
 
 >模型训练：产生训练模型:
+```
 暂时没写
-
+```
 
 >模型评估:RMSE
+```
 暂时没写
-
+```
 
 >结果预测：
 ```python