add mlcourse.ai stickers

jerrypaulsam · May 21, 2019 · e42d220 · e42d220
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diff --git a/jupyter_chinese/assignments_demo/assignment01-人口收入普查数据探索.ipynb b/jupyter_chinese/assignments_demo/assignment01-人口收入普查数据探索.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"../../img/ods_stickers.jpg\" />"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/jupyter_chinese/assignments_demo/assignment02-心血管疾病数据探索分析.ipynb b/jupyter_chinese/assignments_demo/assignment02-心血管疾病数据探索分析.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"../../img/ods_stickers.jpg\" />"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {

diff --git a/jupyter_chinese/assignments_demo/assignment03-决策树和随机森林分析应用.ipynb b/jupyter_chinese/assignments_demo/assignment03-决策树和随机森林分析应用.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"../../img/ods_stickers.jpg\" />"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/jupyter_chinese/assignments_demo/assignment04-逻辑回归用于讽刺文本检测.ipynb b/jupyter_chinese/assignments_demo/assignment04-逻辑回归用于讽刺文本检测.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"../../img/ods_stickers.jpg\" />"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/jupyter_chinese/assignments_demo/assignment05-构建信用评分预测分类模型.ipynb b/jupyter_chinese/assignments_demo/assignment05-构建信用评分预测分类模型.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"../../img/ods_stickers.jpg\" />"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/jupyter_chinese/assignments_demo/assignment06-红酒质量数据回归探索.ipynb b/jupyter_chinese/assignments_demo/assignment06-红酒质量数据回归探索.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"../../img/ods_stickers.jpg\" />"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/jupyter_chinese/assignments_demo/assignment07-非监督学习应用练习.ipynb b/jupyter_chinese/assignments_demo/assignment07-非监督学习应用练习.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"../../img/ods_stickers.jpg\" />"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/jupyter_chinese/assignments_demo/assignment08-线性回归和随机梯度下降.ipynb b/jupyter_chinese/assignments_demo/assignment08-线性回归和随机梯度下降.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"../../img/ods_stickers.jpg\" />"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {

diff --git a/jupyter_chinese/assignments_demo/assignment09-时间序列分析应用练习.ipynb b/jupyter_chinese/assignments_demo/assignment09-时间序列分析应用练习.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"../../img/ods_stickers.jpg\" />"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/jupyter_chinese/topic01-使用-Pandas-进行数据探索.ipynb b/jupyter_chinese/topic01-使用-Pandas-进行数据探索.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"../img/ods_stickers.jpg\" />"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -57,7 +64,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<div style=\"background-color: #FFEAC9; margin-bottom: 10px; padding: 2%; border-radius: 6px;\"><p style=\"line-height: 1.5; font-weight: bold;\"> 中文版本说明</p><p style=\"line-height: 1.5;\">本课程中文版本是经由原作者授权 <a href=\"https://www.shiyanlou.com\"><i class=\"fa fa-external-link-square\" aria-hidden=\"true\"> 实验楼</i></a> 编译制作，你可以到 <a href=\"https://www.shiyanlou.com/courses/1283\"><i class=\"fa fa-external-link-square\" aria-hidden=\"true\"> 实验楼课程页面</i></a> 一键启动 Jupyter Notebook 环境学习，若有疑问欢迎到课程页面提出，我们会及时修订。</p></div>"
+    "<div style=\"background-color: #FFEAC9; margin-bottom: 10px; padding: 2%; border-radius: 6px;\"><p style=\"line-height: 1.5; font-weight: bold;\"> 中文版本说明</p><p style=\"line-height: 1.5;\">本课程中文版本是经由原作者授权 <a href=\"https://www.shiyanlou.com\"><i class=\"fa fa-external-link-square\" aria-hidden=\"true\"> 实验楼</i></a> 编译制作，你可以到 <a href=\"https://www.shiyanlou.com/courses/1283\"><i class=\"fa fa-external-link-square\" aria-hidden=\"true\"> 实验楼课程页面</i></a> 一键启动 Jupyter Notebook 环境学习，若有疑问欢迎到课程页面提出，我们会及时修订。中文版本分发需在遵循原开源协议基础上保留实验楼作为译者署名及链接。</p></div>"
    ]
   },
   {

diff --git a/jupyter_chinese/topic02-Python-数据可视化分析.ipynb b/jupyter_chinese/topic02-Python-数据可视化分析.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"../img/ods_stickers.jpg\" />"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/jupyter_chinese/topic03-决策树和-K-近邻分类.ipynb b/jupyter_chinese/topic03-决策树和-K-近邻分类.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"../img/ods_stickers.jpg\" />"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/jupyter_chinese/topic04-线性回归和线性分类器.ipynb b/jupyter_chinese/topic04-线性回归和线性分类器.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"../img/ods_stickers.jpg\" />"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/jupyter_chinese/topic05-集成学习和随机森林方法.ipynb b/jupyter_chinese/topic05-集成学习和随机森林方法.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"../img/ods_stickers.jpg\" />"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/jupyter_chinese/topic06-特征工程和特征选择.ipynb b/jupyter_chinese/topic06-特征工程和特征选择.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"../img/ods_stickers.jpg\" />"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/jupyter_chinese/topic07-主成分分析和聚类.ipynb b/jupyter_chinese/topic07-主成分分析和聚类.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"../img/ods_stickers.jpg\" />"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/jupyter_chinese/topic08-随机梯度下降和独热编码.ipynb b/jupyter_chinese/topic08-随机梯度下降和独热编码.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"../img/ods_stickers.jpg\" />"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/jupyter_chinese/topic09-时间序列处理与应用.ipynb b/jupyter_chinese/topic09-时间序列处理与应用.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"../img/ods_stickers.jpg\" />"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},