fix(4.2): 代码块

 fix(4.2): 代码块

4.人工智能/4.2机器学习（AI）快速入门（quick start）.md

@@ -84,20 +84,23 @@
 
 ```python
 def estimate_house_sales_price(num_of_bedrooms, sqft, neighborhood):
-  price = 0  # In my area, the average house costs $200 per sqft
-  price_per_sqft = 200  if neighborhood == "hipsterton":
+	price = 0  # In my area, the average house costs $200 per sqft
+	price_per_sqft = 200  
+	if neighborhood == "hipsterton":
     # but some areas cost a bit more
-    price_per_sqft = 400  elif neighborhood == "skid row":
+		price_per_sqft = 400
+	elif neighborhood == "skid row":
     # and some areas cost less
-    price_per_sqft = 100  # start with a base price estimate based on how big the place is
-  price = price_per_sqft * sqft  # now adjust our estimate based on the number of bedrooms
-  if num_of_bedrooms == 0:
-    # Studio apartments are cheap
-    price = price — 20000
-  else:
+		price_per_sqft = 100  # start with a base price estimate based on how big the place is
+	price = price_per_sqft * sqft  # now adjust our estimate based on the number of bedrooms
+	if num_of_bedrooms == 0:
+	# Studio apartments are cheap
+		price = price - 20000
+	else:
     # places with more bedrooms are usually
     # more valuable
-    price = price + (num_of_bedrooms * 1000) return price
+		price = price + (num_of_bedrooms * 1000)
+	return price
 ```
 
 假如你像这样瞎忙几个小时，最后也许会得到一些像模像样的东西。但是永远感觉差点东西。
@@ -110,7 +113,8 @@ def estimate_house_sales_price(num_of_bedrooms, sqft, neighborhood):
 
 ```python
 def estimate_house_sales_price(num_of_bedrooms, sqft, neighborhood):
-  price = <电脑电脑快显灵>  return price
+    price = <电脑电脑快显灵>  
+    return price
 ```
 
 如果你可以找到这么一个公式：
@@ -125,11 +129,12 @@ Y(房价)=W(参数）*X1（卧室数量）+W*X2（面积）+W*X3（地段）
 
 ```python
 def estimate_house_sales_price(num_of_bedrooms, sqft, neighborhood):
-  price = 0  # a little pinch of this
-  price += num_of_bedrooms *<strong> 1.0</strong>  # and a big pinch of that
-  price += sqft * <strong>1.0</strong>  # maybe a handful of this
-  price += neighborhood * <strong>1.0</strong>  # and finally, just a little extra salt for good measure
-  price += <strong>1.0</strong>  return price
+    price = 0  # a little pinch of this
+    price += num_of_bedrooms *1.0  # and a big pinch of that
+    price += sqft * 1.0 # maybe a handful of this
+    price += neighborhood * 1.0  # and finally, just a little extra salt for good measure
+    price += 1.0  
+    return price
 ```
 
 第二步把每个数值都带入进行运算。
@@ -211,11 +216,11 @@ def estimate_house_sales_price(num_of_bedrooms, sqft, neighborhood):
 
 ```python
 def estimate_house_sales_price(num_of_bedrooms, sqft, neighborhood):
- price = 0# a little pinch of this
- price += num_of_bedrooms * 0.123# and a big pinch of that
- price += sqft * 0.41# maybe a handful of this
- price += neighborhood * 0.57
- return price
+    price = 0# a little pinch of this
+    price += num_of_bedrooms * 0.123# and a big pinch of that
+    price += sqft * 0.41# maybe a handful of this
+    price += neighborhood * 0.57
+    return price
 ```
 
 我们换一个好看的形式给他展示
@@ -329,9 +334,11 @@ print('y_pred=',y_test.data)
 
 ```python
 model = Sequential([Dense(32, input_shape=(784,)), 
-  Activation('relu'),Dense(10),Activation('softmax')])# 你也可以通过 .add() 方法简单地添加层：  model = Sequential() 
-  model.add(Dense(32, input_dim=784)) 
-  model.add(Activation('relu'))# 激活函数，你可以理解为加上这个东西可以让他效果更好
+  Activation('relu'),Dense(10),Activation('softmax')])
+# 你也可以通过 .add() 方法简单地添加层：  
+model = Sequential() 
+model.add(Dense(32, input_dim=784)) 
+model.add(Activation('relu'))# 激活函数，你可以理解为加上这个东西可以让他效果更好
 ```
 
 虽然我们的神经网络要比上次大得多（这次有 324 个输入，上次只有 3 个！），但是现在的计算机一眨眼的功夫就能够对这几百个节点进行运算。当然，你的手机也可以做到。