From b00c20bf395634035726b98349b875412c2e75a8 Mon Sep 17 00:00:00 2001
From: 46135621 <985579956@qq.com>
Date: Thu, 20 Apr 2023 02:08:35 +0800
Subject: [PATCH] =?UTF-8?q?fix(4.2):=E4=BB=A3=E7=A0=81=E5=9D=97?=
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---
...（AI）快速入门（quick start）.md | 55 +++++++++++--------
1 file changed, 31 insertions(+), 24 deletions(-)
diff --git a/4.人工智能/4.2机器学习（AI）快速入门（quick start）.md b/4.人工智能/4.2机器学习（AI）快速入门（quick start）.md
index 5376fd1..4d167c6 100644
--- a/4.人工智能/4.2机器学习（AI）快速入门（quick start）.md
+++ b/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 * 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
+ 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。