Merge branch 'master' into development

Author: Jared Weed

projects/boston_housing/README.md

@@ -11,7 +11,7 @@ This project requires **Python 2.7** and the following Python libraries installe
 
 You will also need to have software installed to run and execute an [iPython Notebook](http://ipython.org/notebook.html)
 
-Udacity recommends our students install [Anaconda](https://www.continuum.io/downloads), i pre-packaged Python distribution that contains all of the necessary libraries and software for this project. 
+Udacity recommends our students install [Anaconda](https://www.continuum.io/downloads), a pre-packaged Python distribution that contains all of the necessary libraries and software for this project. 
 
 ### Code
 

projects/creating_customer_segments/README.md

@@ -12,7 +12,7 @@ This project requires **Python 2.7** and the following Python libraries installe
 
 You will also need to have software installed to run and execute an [iPython Notebook](http://ipython.org/notebook.html)
 
-Udacity recommends our students install [Anaconda](https://www.continuum.io/downloads), i pre-packaged Python distribution that contains all of the necessary libraries and software for this project. 
+Udacity recommends our students install [Anaconda](https://www.continuum.io/downloads), a pre-packaged Python distribution that contains all of the necessary libraries and software for this project. 
 
 ### Code
 
@@ -29,4 +29,4 @@ This will open the iPython Notebook software and project file in your browser.
 
 ## Data
 
-The dataset used in this project is included as `customers.csv`. You can find more information on this dataset on the [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/datasets/Wholesale+customers) page.
+The dataset used in this project is included as `customers.csv`. You can find more information on this dataset on the [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/datasets/Wholesale+customers) page.

projects/smartcab/README.md

@@ -14,7 +14,7 @@ Template code is provided in the `smartcab/agent.py` python file. Additional sup
 
 In a terminal or command window, navigate to the top-level project directory `smartcab/` (that contains this README) and run one of the following commands:
 
-```python smartcab/agent.py```
+```python smartcab/agent.py```  
 ```python -m smartcab.agent```
 
 This will run the `agent.py` file and execute your agent code.

projects/student_intervention/README.md

@@ -11,7 +11,7 @@ This project requires **Python 2.7** and the following Python libraries installe
 
 You will also need to have software installed to run and execute an [iPython Notebook](http://ipython.org/notebook.html)
 
-Udacity recommends our students install [Anaconda](https://www.continuum.io/downloads), i pre-packaged Python distribution that contains all of the necessary libraries and software for this project. 
+Udacity recommends our students install [Anaconda](https://www.continuum.io/downloads), a pre-packaged Python distribution that contains all of the necessary libraries and software for this project. 
 
 ### Code
 
@@ -30,34 +30,34 @@ This will open the iPython Notebook software and project file in your browser.
 
 The dataset used in this project is included as `student-data.csv`. This dataset has the following attributes:
 
-- `school` ? student's school (binary: "GP" or "MS")
-- `sex` ? student's sex (binary: "F" - female or "M" - male)
-- `age` ? student's age (numeric: from 15 to 22)
-- `address` ? student's home address type (binary: "U" - urban or "R" - rural)
-- `famsize` ? family size (binary: "LE3" - less or equal to 3 or "GT3" - greater than 3)
-- `Pstatus` ? parent's cohabitation status (binary: "T" - living together or "A" - apart)
-- `Medu` ? mother's education (numeric: 0 - none,  1 - primary education (4th grade), 2 -€“ 5th to 9th grade, 3 - secondary education or 4 -€“ higher education)
-- `Fedu` ? father's education (numeric: 0 - none,  1 - primary education (4th grade), 2 - 5th to 9th grade, 3 - secondary education or 4 -€“ higher education)
-- `Mjob` ? mother's job (nominal: "teacher", "health" care related, civil "services" (e.g. administrative or police), "at_home" or "other")
-- `Fjob` ? father's job (nominal: "teacher", "health" care related, civil "services" (e.g. administrative or police), "at_home" or "other")
-- `reason` ? reason to choose this school (nominal: close to "home", school "reputation", "course" preference or "other")
-- `guardian` ? student's guardian (nominal: "mother", "father" or "other")
-- `traveltime` ? home to school travel time (numeric: 1 - <15 min., 2 - 15 to 30 min., 3 - 30 min. to 1 hour, or 4 - >1 hour)
-- `studytime` ? weekly study time (numeric: 1 - <2 hours, 2 - 2 to 5 hours, 3 - 5 to 10 hours, or 4 - >10 hours)
-- `failures` ? number of past class failures (numeric: n if 1<=n<3, else 4)
-- `schoolsup` ? extra educational support (binary: yes or no)
-- `famsup` ? family educational support (binary: yes or no)
-- `paid` ? extra paid classes within the course subject (Math or Portuguese) (binary: yes or no)
-- `activities` ? extra-curricular activities (binary: yes or no)
-- `nursery` ? attended nursery school (binary: yes or no)
-- `higher` ? wants to take higher education (binary: yes or no)
-- `internet` ? Internet access at home (binary: yes or no)
-- `romantic` ? with a romantic relationship (binary: yes or no)
-- `famrel` ? quality of family relationships (numeric: from 1 - very bad to 5 - excellent)
-- `freetime` ? free time after school (numeric: from 1 - very low to 5 - very high)
-- `goout` ? going out with friends (numeric: from 1 - very low to 5 - very high)
-- `Dalc` ? workday alcohol consumption (numeric: from 1 - very low to 5 - very high)
-- `Walc` ? weekend alcohol consumption (numeric: from 1 - very low to 5 - very high)
-- `health` ? current health status (numeric: from 1 - very bad to 5 - very good)
-- `absences` ? number of school absences (numeric: from 0 to 93)
-- `passed` ? did the student pass the final exam (binary: yes or no)
+- `school` : student's school (binary: "GP" or "MS")
+- `sex` : student's sex (binary: "F" - female or "M" - male)
+- `age` : student's age (numeric: from 15 to 22)
+- `address` : student's home address type (binary: "U" - urban or "R" - rural)
+- `famsize` : family size (binary: "LE3" - less or equal to 3 or "GT3" - greater than 3)
+- `Pstatus` : parent's cohabitation status (binary: "T" - living together or "A" - apart)
+- `Medu` : mother's education (numeric: 0 - none,  1 - primary education (4th grade), 2 - 5th to 9th grade, 3 - secondary education or 4 - higher education)
+- `Fedu` : father's education (numeric: 0 - none,  1 - primary education (4th grade), 2 - 5th to 9th grade, 3 - secondary education or 4 - higher education)
+- `Mjob` : mother's job (nominal: "teacher", "health" care related, civil "services" (e.g. administrative or police), "at_home" or "other")
+- `Fjob` : father's job (nominal: "teacher", "health" care related, civil "services" (e.g. administrative or police), "at_home" or "other")
+- `reason` : reason to choose this school (nominal: close to "home", school "reputation", "course" preference or "other")
+- `guardian` : student's guardian (nominal: "mother", "father" or "other")
+- `traveltime` : home to school travel time (numeric: 1 - <15 min., 2 - 15 to 30 min., 3 - 30 min. to 1 hour, or 4 - >1 hour)
+- `studytime` : weekly study time (numeric: 1 - <2 hours, 2 - 2 to 5 hours, 3 - 5 to 10 hours, or 4 - >10 hours)
+- `failures` : number of past class failures (numeric: n if 1<=n<3, else 4)
+- `schoolsup` : extra educational support (binary: yes or no)
+- `famsup` : family educational support (binary: yes or no)
+- `paid` : extra paid classes within the course subject (Math or Portuguese) (binary: yes or no)
+- `activities` : extra-curricular activities (binary: yes or no)
+- `nursery` : attended nursery school (binary: yes or no)
+- `higher` : wants to take higher education (binary: yes or no)
+- `internet` : Internet access at home (binary: yes or no)
+- `romantic` : with a romantic relationship (binary: yes or no)
+- `famrel` : quality of family relationships (numeric: from 1 - very bad to 5 - excellent)
+- `freetime` : free time after school (numeric: from 1 - very low to 5 - very high)
+- `goout` : going out with friends (numeric: from 1 - very low to 5 - very high)
+- `Dalc` : workday alcohol consumption (numeric: from 1 - very low to 5 - very high)
+- `Walc` : weekend alcohol consumption (numeric: from 1 - very low to 5 - very high)
+- `health` : current health status (numeric: from 1 - very bad to 5 - very good)
+- `absences` : number of school absences (numeric: from 0 to 93)
+- `passed` : did the student pass the final exam (binary: yes or no)

projects/titanic_survival_exploration/Titanic_Survival_Exploration.ipynb

@@ -290,7 +290,7 @@
     "collapsed": true
    },
    "source": [
-    "Examining the survival statistics, the majority of males younger then 10 survived the ship sinking, whereas most males age 10 or older *did not survive* the ship sinking. Let's continue to build on our previous prediction: If a passenger was female, then we will predict they survive. If a passenger was male and younger than 10, then we will also predict they survive. Otherwise, we will predict they do not survive.  \n",
+    "Examining the survival statistics, the majority of males younger than 10 survived the ship sinking, whereas most males age 10 or older *did not survive* the ship sinking. Let's continue to build on our previous prediction: If a passenger was female, then we will predict they survive. If a passenger was male and younger than 10, then we will also predict they survive. Otherwise, we will predict they do not survive.  \n",
     "Fill in the missing code below so that the function will make this prediction.  \n",
     "**Hint:** You can start your implementation of this function using the prediction code you wrote earlier from `predictions_1`."
    ]

projects_cn/titanic_survival_exploration/README.md

@@ -0,0 +1,44 @@
+# 项目 0: 入门与基础
+## 预测泰坦尼克号乘客幸存率
+
+### 安装要求
+这个项目要求使用 **Python 2.7** 以及安装下列python库
+
+- [NumPy](http://www.numpy.org/)
+- [Pandas](http://pandas.pydata.org)
+- [matplotlib](http://matplotlib.org/)
+- [scikit-learn](http://scikit-learn.org/stable/)
+  ​
+
+你还需要安装和运行 [Jupyter Notebook](http://jupyter.readthedocs.io/en/latest/install.html#optional-for-experienced-python-developers-installing-jupyter-with-pip)。
+
+
+优达学城推荐学生安装 [Anaconda](https://www.continuum.io/downloads)，一个包含了项目需要的所有库和软件的 Python 发行版本。
+
+### 代码
+​
+事例代码在 `titanic_survival_exploration_cn.ipynb` 文件中，辅助代码在 `titanic_visualizations.py` 文件中。尽管已经提供了一些代码帮助你上手，你还是需要补充些代码使得项目要求的功能能够成功实现。
+
+### 运行
+​
+在命令行中，确保当前目录为 `titanic_survival_exploration/` 文件夹的最顶层（目录包含本 README 文件），运行下列命令。
+​
+```jupyter notebook titanic_survival_exploration.ipynb```
+​
+这会启动 Jupyter Notebook 把项目文件打开在你的浏览器中。
+​
+### 数据
+​
+这个项目的数据包含在 `titanic_data.csv` 文件中。文件包含下列特征：
+​
+- **Survived**：是否存活（0代表否，1代表是）
+- **Pclass**：社会阶级（1代表上层阶级，2代表中层阶级，3代表底层阶级）
+- **Name**：船上乘客的名字
+- **Sex**：船上乘客的性别
+- **Age**：船上乘客的年龄（可能存在 `NaN`）
+- **SibSp**：乘客在船上的兄弟姐妹和配偶的数量
+- **Parch**：乘客在船上的父母以及小孩的数量
+- **Ticket**：乘客船票的编号
+- **Fare**：乘客为船票支付的费用
+- **Cabin**：乘客所在船舱的编号（可能存在 `NaN`）
+- **Embarked**：乘客上船的港口（C 代表从 Cherbourg 登船，Q 代表从 Queenstown 登船，S 代表从 Southampton 登船）