diff --git a/README.md b/README.md
index 1d01a22..2d5a776 100644
--- a/README.md
+++ b/README.md
@@ -1,38 +1,41 @@
-
- 
+
+ 
----
-我是 周沫凡, [莫烦Python](https://morvanzhou.github.io/about/) 只是谐音, 我喜欢制作,
-分享所学的东西, 所以你能在这里找到很多有用的东西, 少走弯路. 你能在[这里](https://morvanzhou.github.io/about/)找到关于我的所有东西.
+我是 周沫凡, [莫烦Python](https://mofanpy.com/) 只是谐音, 我喜欢制作,
+分享所学的东西, 所以你能在这里找到很多有用的东西, 少走弯路. 你能在[这里](https://mofanpy.com/about/)找到关于我的所有东西.
## 这个 Python tutorial 的一些内容:
-* [Python 基础](https://morvanzhou.github.io/tutorials/python-basic/)
- * [基础](https://morvanzhou.github.io/tutorials/python-basic/basic/)
- * [多线程 threading](https://morvanzhou.github.io/tutorials/python-basic/threading/)
- * [多进程 multiprocessing](https://morvanzhou.github.io/tutorials/python-basic/multiprocessing/)
- * [简单窗口 tkinter](https://morvanzhou.github.io/tutorials/python-basic/tkinter/)
-* [机器学习](https://morvanzhou.github.io/tutorials/machine-learning/)
- * [有趣的机器学习](https://morvanzhou.github.io/tutorials/machine-learning/ML-intro/)
- * [强化学习 (Reinforcement Learning)](https://morvanzhou.github.io/tutorials/machine-learning/reinforcement-learning/)
- * [Tensorflow (神经网络)](https://morvanzhou.github.io/tutorials/machine-learning/tensorflow/)
- * [PyTorch (神经网络)](https://morvanzhou.github.io/tutorials/machine-learning/torch/)
- * [Theano (神经网络)](https://morvanzhou.github.io/tutorials/machine-learning/theano/)
- * [Keras (快速神经网络)](https://morvanzhou.github.io/tutorials/machine-learning/keras/)
- * [Scikit-Learn (机器学习)](https://morvanzhou.github.io/tutorials/machine-learning/sklearn/)
-* [数据处理](https://morvanzhou.github.io/tutorials/data-manipulation/)
- * [Numpy & Pandas (处理数据)](https://morvanzhou.github.io/tutorials/data-manipulation/np-pd/)
- * [Matplotlib (绘图)](https://morvanzhou.github.io/tutorials/data-manipulation/plt/)
-* [其他](https://morvanzhou.github.io/tutorials/others/)
- * [Git (版本管理)](https://morvanzhou.github.io/tutorials/others/git/)
+* [Python 基础](https://mofanpy.com/tutorials/python-basic/)
+ * [基础](https://mofanpy.com/tutorials/python-basic/basic/)
+ * [多线程 threading](https://mofanpy.com/tutorials/python-basic/threading/)
+ * [多进程 multiprocessing](https://mofanpy.com/tutorials/python-basic/multiprocessing/)
+ * [简单窗口 tkinter](https://mofanpy.com/tutorials/python-basic/tkinter/)
+* [机器学习](https://mofanpy.com/tutorials/machine-learning/)
+ * [有趣的机器学习](https://mofanpy.com/tutorials/machine-learning/ML-intro/)
+ * [强化学习 (Reinforcement Learning)](https://mofanpy.com/tutorials/machine-learning/reinforcement-learning/)
+ * [进化算法 (Evolutionary Algorithm) 如遗传算法等](https://mofanpy.com/tutorials/machine-learning/evolutionary-algorithm/)
+ * [Tensorflow (神经网络)](https://mofanpy.com/tutorials/machine-learning/tensorflow/)
+ * [PyTorch (神经网络)](https://mofanpy.com/tutorials/machine-learning/torch/)
+ * [Theano (神经网络)](https://mofanpy.com/tutorials/machine-learning/theano/)
+ * [Keras (快速神经网络)](https://mofanpy.com/tutorials/machine-learning/keras/)
+ * [Scikit-Learn (机器学习)](https://mofanpy.com/tutorials/machine-learning/sklearn/)
+ * [机器学习实战](https://mofanpy.com/tutorials/machine-learning/ML-practice/)
+* [数据处理](https://mofanpy.com/tutorials/data-manipulation/)
+ * [Numpy & Pandas (处理数据)](https://mofanpy.com/tutorials/data-manipulation/np-pd/)
+ * [Matplotlib (绘图)](https://mofanpy.com/tutorials/data-manipulation/plt/)
+ * [爬虫](https://mofanpy.com/tutorials/data-manipulation/scraping/)
+* [其他](https://mofanpy.com/tutorials/others/)
+ * [Git (版本管理)](https://mofanpy.com/tutorials/others/git/)
+ * [Linux 简易教学](https://mofanpy.com/tutorials/others/linux-basic/)
## 赞助和支持
这些 tutorial 都是我用业余时间写出来, 录成视频, 如果你觉得它对你很有帮助, 请你也分享给需要学习的朋友们.
-如果你看好我的经验分享, 也请考虑适当的 [赞助打赏](https://morvanzhou.github.io/support/), 让我能继续分享更好的内容给大家.
\ No newline at end of file
+如果你看好我的经验分享, 也请考虑适当的 [赞助打赏](https://mofanpy.com/support/), 让我能继续分享更好的内容给大家.
\ No newline at end of file
diff --git a/Reinforcement_learning_TUT/README.md b/Reinforcement_learning_TUT/README.md
index 38fccff..773ed30 100644
--- a/Reinforcement_learning_TUT/README.md
+++ b/Reinforcement_learning_TUT/README.md
@@ -1,6 +1,6 @@
- 
+ 
@@ -10,11 +10,11 @@
# Note! This Reinforcement Learning Tutorial has been moved to anther independent repo:
-[https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow)
+[/MorvanZhou/Reinforcement-learning-with-tensorflow](/MorvanZhou/Reinforcement-learning-with-tensorflow)
# 请注意! 这个 强化学习 的教程代码已经被移至另一个网页:
-[https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow)
+[/MorvanZhou/Reinforcement-learning-with-tensorflow](/MorvanZhou/Reinforcement-learning-with-tensorflow)
# Donation
@@ -31,7 +31,7 @@
diff --git a/basic/.ipynb_checkpoints/36_regex-checkpoint.ipynb b/basic/.ipynb_checkpoints/36_regex-checkpoint.ipynb
new file mode 100644
index 0000000..984c91f
--- /dev/null
+++ b/basic/.ipynb_checkpoints/36_regex-checkpoint.ipynb
@@ -0,0 +1,648 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Python 正则表达 RegEx"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 导入模块"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import re"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 简单 Python 匹配"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "True\n",
+ "False\n"
+ ]
+ }
+ ],
+ "source": [
+ "# matching string\n",
+ "pattern1 = \"cat\"\n",
+ "pattern2 = \"bird\"\n",
+ "string = \"dog runs to cat\"\n",
+ "print(pattern1 in string) \n",
+ "print(pattern2 in string) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 用正则寻找配对"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(12, 15), match='cat'>\n",
+ "None\n"
+ ]
+ }
+ ],
+ "source": [
+ "# regular expression\n",
+ "pattern1 = \"cat\"\n",
+ "pattern2 = \"bird\"\n",
+ "string = \"dog runs to cat\"\n",
+ "print(re.search(pattern1, string)) \n",
+ "print(re.search(pattern2, string)) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 匹配多种可能 使用 []"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(4, 7), match='run'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# multiple patterns (\"run\" or \"ran\")\n",
+ "ptn = r\"r[au]n\" \n",
+ "print(re.search(ptn, \"dog runs to cat\")) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 匹配更多种可能"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "None\n",
+ "<_sre.SRE_Match object; span=(4, 7), match='run'>\n",
+ "<_sre.SRE_Match object; span=(4, 7), match='r2n'>\n",
+ "<_sre.SRE_Match object; span=(4, 7), match='run'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# continue\n",
+ "print(re.search(r\"r[A-Z]n\", \"dog runs to cat\")) \n",
+ "print(re.search(r\"r[a-z]n\", \"dog runs to cat\")) \n",
+ "print(re.search(r\"r[0-9]n\", \"dog r2ns to cat\")) \n",
+ "print(re.search(r\"r[0-9a-z]n\", \"dog runs to cat\")) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 特殊种类匹配"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### 数字"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(4, 7), match='r4n'>\n",
+ "<_sre.SRE_Match object; span=(0, 3), match='run'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# \\d : decimal digit\n",
+ "print(re.search(r\"r\\dn\", \"run r4n\")) \n",
+ "# \\D : any non-decimal digit\n",
+ "print(re.search(r\"r\\Dn\", \"run r4n\")) \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### 空白"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(0, 3), match='r\\nn'>\n",
+ "<_sre.SRE_Match object; span=(4, 7), match='r4n'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# \\s : any white space [\\t\\n\\r\\f\\v]\n",
+ "print(re.search(r\"r\\sn\", \"r\\nn r4n\")) \n",
+ "# \\S : opposite to \\s, any non-white space\n",
+ "print(re.search(r\"r\\Sn\", \"r\\nn r4n\")) \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### 所有字母数字和\"_\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(4, 7), match='r4n'>\n",
+ "<_sre.SRE_Match object; span=(0, 3), match='r\\nn'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# \\w : [a-zA-Z0-9_]\n",
+ "print(re.search(r\"r\\wn\", \"r\\nn r4n\")) \n",
+ "# \\W : opposite to \\w\n",
+ "print(re.search(r\"r\\Wn\", \"r\\nn r4n\")) \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### 空白字符"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(4, 8), match='runs'>\n",
+ "<_sre.SRE_Match object; span=(5, 11), match=' runs '>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# \\b : empty string (only at the start or end of the word)\n",
+ "print(re.search(r\"\\bruns\\b\", \"dog runs to cat\")) \n",
+ "# \\B : empty string (but not at the start or end of a word)\n",
+ "print(re.search(r\"\\B runs \\B\", \"dog runs to cat\")) \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### 特殊字符 任意字符"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(0, 5), match='runs\\\\'>\n",
+ "<_sre.SRE_Match object; span=(0, 3), match='r[n'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# \\\\ : match \\\n",
+ "print(re.search(r\"runs\\\\\", \"runs\\ to me\")) \n",
+ "# . : match anything (except \\n)\n",
+ "print(re.search(r\"r.n\", \"r[ns to me\")) \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### 句尾句首"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(0, 3), match='dog'>\n",
+ "<_sre.SRE_Match object; span=(12, 15), match='cat'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# ^ : match line beginning\n",
+ "print(re.search(r\"^dog\", \"dog runs to cat\")) \n",
+ "# $ : match line ending\n",
+ "print(re.search(r\"cat$\", \"dog runs to cat\")) \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### 是否"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(0, 6), match='Monday'>\n",
+ "<_sre.SRE_Match object; span=(0, 3), match='Mon'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# ? : may or may not occur\n",
+ "print(re.search(r\"Mon(day)?\", \"Monday\")) \n",
+ "print(re.search(r\"Mon(day)?\", \"Mon\")) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 多行匹配"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "None\n",
+ "<_sre.SRE_Match object; span=(18, 19), match='I'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# multi-line\n",
+ "string = \"\"\"\n",
+ "dog runs to cat.\n",
+ "I run to dog.\n",
+ "\"\"\"\n",
+ "print(re.search(r\"^I\", string)) \n",
+ "print(re.search(r\"^I\", string, flags=re.M)) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 0或多次"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(0, 1), match='a'>\n",
+ "<_sre.SRE_Match object; span=(0, 6), match='abbbbb'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# * : occur 0 or more times\n",
+ "print(re.search(r\"ab*\", \"a\")) \n",
+ "print(re.search(r\"ab*\", \"abbbbb\")) \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 1或多次"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "None\n",
+ "<_sre.SRE_Match object; span=(0, 6), match='abbbbb'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# + : occur 1 or more times\n",
+ "print(re.search(r\"ab+\", \"a\")) \n",
+ "print(re.search(r\"ab+\", \"abbbbb\")) \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 可选次数"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "None\n",
+ "<_sre.SRE_Match object; span=(0, 6), match='abbbbb'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# {n, m} : occur n to m times\n",
+ "print(re.search(r\"ab{2,10}\", \"a\")) \n",
+ "print(re.search(r\"ab{2,10}\", \"abbbbb\")) \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## group 组"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "021523, Date: Feb/12/2017\n",
+ "021523\n",
+ "Feb/12/2017\n"
+ ]
+ }
+ ],
+ "source": [
+ "# group\n",
+ "match = re.search(r\"(\\d+), Date: (.+)\", \"ID: 021523, Date: Feb/12/2017\")\n",
+ "print(match.group()) \n",
+ "print(match.group(1)) \n",
+ "print(match.group(2)) "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "021523\n",
+ "Feb/12/2017\n"
+ ]
+ }
+ ],
+ "source": [
+ "match = re.search(r\"(?P\\d+), Date: (?P.+)\", \"ID: 021523, Date: Feb/12/2017\")\n",
+ "print(match.group('id')) \n",
+ "print(match.group('date')) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 寻找所有匹配 "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "['run', 'ran']\n"
+ ]
+ }
+ ],
+ "source": [
+ "# findall\n",
+ "print(re.findall(r\"r[ua]n\", \"run ran ren\")) "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "['run', 'ran']\n"
+ ]
+ }
+ ],
+ "source": [
+ "# | : or\n",
+ "print(re.findall(r\"(run|ran)\", \"run ran ren\")) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 替换"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 22,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "dog catches to cat\n"
+ ]
+ }
+ ],
+ "source": [
+ "# re.sub() replace\n",
+ "print(re.sub(r\"r[au]ns\", \"catches\", \"dog runs to cat\")) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 分裂"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 23,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "['a', 'b', 'c', 'd', 'e']\n"
+ ]
+ }
+ ],
+ "source": [
+ "# re.split()\n",
+ "print(re.split(r\"[,;\\.]\", \"a;b,c.d;e\")) \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## compile"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 24,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(4, 7), match='ran'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# compile\n",
+ "compiled_re = re.compile(r\"r[ua]n\")\n",
+ "print(compiled_re.search(\"dog ran to cat\")) "
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.5.1"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/basic/35_set.py b/basic/35_set.py
index 8df852b..31340da 100644
--- a/basic/35_set.py
+++ b/basic/35_set.py
@@ -10,17 +10,20 @@
print(set(char_list))
print(set(sentence))
-print(set([char_list, sentence]))
+print(set(char_list + list(sentence)))
unique_char = set(char_list)
unique_char.add('x')
-unique_char.add(['y', 'z'])
+# unique_char.add(['y', 'z']) this is wrong
print(unique_char)
+unique_char.remove('x')
+print(unique_char)
+unique_char.discard('d')
+print(unique_char)
unique_char.clear()
print(unique_char)
-print(char_list.discard('d'))
-print(char_list.remove('d'))
-print(char_list.difference({'a', 'e', 'i'}))
-print(char_list.intersection({'a', 'e', 'i'}))
\ No newline at end of file
+unique_char = set(char_list)
+print(unique_char.difference({'a', 'e', 'i'}))
+print(unique_char.intersection({'a', 'e', 'i'}))
\ No newline at end of file
diff --git a/basic/36_RegEx.py b/basic/36_RegEx.py
new file mode 100644
index 0000000..b68dd3a
--- /dev/null
+++ b/basic/36_RegEx.py
@@ -0,0 +1,110 @@
+import re
+
+# matching string
+pattern1 = "cat"
+pattern2 = "bird"
+string = "dog runs to cat"
+print(pattern1 in string) # True
+print(pattern2 in string) # False
+
+
+# regular expression
+pattern1 = "cat"
+pattern2 = "bird"
+string = "dog runs to cat"
+print(re.search(pattern1, string)) # <_sre.SRE_Match object; span=(12, 15), match='cat'>
+print(re.search(pattern2, string)) # None
+
+
+# multiple patterns ("run" or "ran")
+ptn = r"r[au]n" # start with "r" means raw string
+print(re.search(ptn, "dog runs to cat")) # <_sre.SRE_Match object; span=(4, 7), match='run'>
+
+
+# continue
+print(re.search(r"r[A-Z]n", "dog runs to cat")) # None
+print(re.search(r"r[a-z]n", "dog runs to cat")) # <_sre.SRE_Match object; span=(4, 7), match='run'>
+print(re.search(r"r[0-9]n", "dog r2ns to cat")) # <_sre.SRE_Match object; span=(4, 7), match='r2n'>
+print(re.search(r"r[0-9a-z]n", "dog runs to cat")) # <_sre.SRE_Match object; span=(4, 7), match='run'>
+
+
+# \d : decimal digit
+print(re.search(r"r\dn", "run r4n")) # <_sre.SRE_Match object; span=(4, 7), match='r4n'>
+# \D : any non-decimal digit
+print(re.search(r"r\Dn", "run r4n")) # <_sre.SRE_Match object; span=(0, 3), match='run'>
+# \s : any white space [\t\n\r\f\v]
+print(re.search(r"r\sn", "r\nn r4n")) # <_sre.SRE_Match object; span=(0, 3), match='r\nn'>
+# \S : opposite to \s, any non-white space
+print(re.search(r"r\Sn", "r\nn r4n")) # <_sre.SRE_Match object; span=(4, 7), match='r4n'>
+# \w : [a-zA-Z0-9_]
+print(re.search(r"r\wn", "r\nn r4n")) # <_sre.SRE_Match object; span=(4, 7), match='r4n'>
+# \W : opposite to \w
+print(re.search(r"r\Wn", "r\nn r4n")) # <_sre.SRE_Match object; span=(0, 3), match='r\nn'>
+# \b : empty string (only at the start or end of the word)
+print(re.search(r"\bruns\b", "dog runs to cat")) # <_sre.SRE_Match object; span=(4, 8), match='runs'>
+# \B : empty string (but not at the start or end of a word)
+print(re.search(r"\B runs \B", "dog runs to cat")) # <_sre.SRE_Match object; span=(8, 14), match=' runs '>
+# \\ : match \
+print(re.search(r"runs\\", "runs\ to me")) # <_sre.SRE_Match object; span=(0, 5), match='runs\\'>
+# . : match anything (except \n)
+print(re.search(r"r.n", "r[ns to me")) # <_sre.SRE_Match object; span=(0, 3), match='r[n'>
+# ^ : match line beginning
+print(re.search(r"^dog", "dog runs to cat")) # <_sre.SRE_Match object; span=(0, 3), match='dog'>
+# $ : match line ending
+print(re.search(r"cat$", "dog runs to cat")) # <_sre.SRE_Match object; span=(12, 15), match='cat'>
+# ? : may or may not occur
+print(re.search(r"Mon(day)?", "Monday")) # <_sre.SRE_Match object; span=(0, 6), match='Monday'>
+print(re.search(r"Mon(day)?", "Mon")) # <_sre.SRE_Match object; span=(0, 3), match='Mon'>
+
+
+# multi-line
+string = """
+dog runs to cat.
+I run to dog.
+"""
+print(re.search(r"^I", string)) # None
+print(re.search(r"^I", string, flags=re.M)) # <_sre.SRE_Match object; span=(18, 19), match='I'>
+
+
+# * : occur 0 or more times
+print(re.search(r"ab*", "a")) # <_sre.SRE_Match object; span=(0, 1), match='a'>
+print(re.search(r"ab*", "abbbbb")) # <_sre.SRE_Match object; span=(0, 6), match='abbbbb'>
+
+# + : occur 1 or more times
+print(re.search(r"ab+", "a")) # None
+print(re.search(r"ab+", "abbbbb")) # <_sre.SRE_Match object; span=(0, 6), match='abbbbb'>
+
+# {n, m} : occur n to m times
+print(re.search(r"ab{2,10}", "a")) # None
+print(re.search(r"ab{2,10}", "abbbbb")) # <_sre.SRE_Match object; span=(0, 6), match='abbbbb'>
+
+
+# group
+match = re.search(r"(\d+), Date: (.+)", "ID: 021523, Date: Feb/12/2017")
+print(match.group()) # 021523, Date: Feb/12/2017
+print(match.group(1)) # 021523
+print(match.group(2)) # Date: Feb/12/2017
+
+match = re.search(r"(?P\d+), Date: (?P.+)", "ID: 021523, Date: Feb/12/2017")
+print(match.group('id')) # 021523
+print(match.group('date')) # Date: Feb/12/2017
+
+# findall
+print(re.findall(r"r[ua]n", "run ran ren")) # ['run', 'ran']
+
+# | : or
+print(re.findall(r"(run|ran)", "run ran ren")) # ['run', 'ran']
+
+# re.sub() replace
+print(re.sub(r"r[au]ns", "catches", "dog runs to cat")) # dog catches to cat
+
+# re.split()
+print(re.split(r"[,;\.]", "a;b,c.d;e")) # ['a', 'b', 'c', 'd', 'e']
+
+
+# compile
+compiled_re = re.compile(r"r[ua]n")
+print(compiled_re.search("dog ran to cat")) # <_sre.SRE_Match object; span=(4, 7), match='ran'>
+
+
+
diff --git a/basic/36_regex.ipynb b/basic/36_regex.ipynb
new file mode 100644
index 0000000..52aa22f
--- /dev/null
+++ b/basic/36_regex.ipynb
@@ -0,0 +1,648 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Python 正则表达 RegEx"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 导入模块"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import re"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 简单 Python 匹配"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "True\n",
+ "False\n"
+ ]
+ }
+ ],
+ "source": [
+ "# matching string\n",
+ "pattern1 = \"cat\"\n",
+ "pattern2 = \"bird\"\n",
+ "string = \"dog runs to cat\"\n",
+ "print(pattern1 in string) \n",
+ "print(pattern2 in string) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 用正则寻找配对"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(12, 15), match='cat'>\n",
+ "None\n"
+ ]
+ }
+ ],
+ "source": [
+ "# regular expression\n",
+ "pattern1 = \"cat\"\n",
+ "pattern2 = \"bird\"\n",
+ "string = \"dog runs to cat\"\n",
+ "print(re.search(pattern1, string)) \n",
+ "print(re.search(pattern2, string)) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 匹配多种可能 使用 []"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(4, 7), match='run'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# multiple patterns (\"run\" or \"ran\")\n",
+ "ptn = r\"r[au]n\" \n",
+ "print(re.search(ptn, \"dog runs to cat\")) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 匹配更多种可能"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "None\n",
+ "<_sre.SRE_Match object; span=(4, 7), match='run'>\n",
+ "<_sre.SRE_Match object; span=(4, 7), match='r2n'>\n",
+ "<_sre.SRE_Match object; span=(4, 7), match='run'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# continue\n",
+ "print(re.search(r\"r[A-Z]n\", \"dog runs to cat\")) \n",
+ "print(re.search(r\"r[a-z]n\", \"dog runs to cat\")) \n",
+ "print(re.search(r\"r[0-9]n\", \"dog r2ns to cat\")) \n",
+ "print(re.search(r\"r[0-9a-z]n\", \"dog runs to cat\")) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 特殊种类匹配"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### 数字"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(4, 7), match='r4n'>\n",
+ "<_sre.SRE_Match object; span=(0, 3), match='run'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# \\d : decimal digit\n",
+ "print(re.search(r\"r\\dn\", \"run r4n\")) \n",
+ "# \\D : any non-decimal digit\n",
+ "print(re.search(r\"r\\Dn\", \"run r4n\")) \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### 空白"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(0, 3), match='r\\nn'>\n",
+ "<_sre.SRE_Match object; span=(4, 7), match='r4n'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# \\s : any white space [\\t\\n\\r\\f\\v]\n",
+ "print(re.search(r\"r\\sn\", \"r\\nn r4n\")) \n",
+ "# \\S : opposite to \\s, any non-white space\n",
+ "print(re.search(r\"r\\Sn\", \"r\\nn r4n\")) \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### 所有字母数字和\"_\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(4, 7), match='r4n'>\n",
+ "<_sre.SRE_Match object; span=(0, 3), match='r\\nn'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# \\w : [a-zA-Z0-9_]\n",
+ "print(re.search(r\"r\\wn\", \"r\\nn r4n\")) \n",
+ "# \\W : opposite to \\w\n",
+ "print(re.search(r\"r\\Wn\", \"r\\nn r4n\")) \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### 空白字符"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(4, 8), match='runs'>\n",
+ "<_sre.SRE_Match object; span=(5, 11), match=' runs '>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# \\b : empty string (only at the start or end of the word)\n",
+ "print(re.search(r\"\\bruns\\b\", \"dog runs to cat\")) \n",
+ "# \\B : empty string (but not at the start or end of a word)\n",
+ "print(re.search(r\"\\B runs \\B\", \"dog runs to cat\")) \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### 特殊字符 任意字符"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(0, 5), match='runs\\\\'>\n",
+ "<_sre.SRE_Match object; span=(0, 3), match='r[n'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# \\\\ : match \\\n",
+ "print(re.search(r\"runs\\\\\", \"runs\\ to me\")) \n",
+ "# . : match anything (except \\n)\n",
+ "print(re.search(r\"r.n\", \"r[ns to me\")) \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### 句尾句首"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(0, 3), match='dog'>\n",
+ "<_sre.SRE_Match object; span=(12, 15), match='cat'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# ^ : match line beginning\n",
+ "print(re.search(r\"^dog\", \"dog runs to cat\")) \n",
+ "# $ : match line ending\n",
+ "print(re.search(r\"cat$\", \"dog runs to cat\")) \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### 是否"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(0, 6), match='Monday'>\n",
+ "<_sre.SRE_Match object; span=(0, 3), match='Mon'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# ? : may or may not occur\n",
+ "print(re.search(r\"Mon(day)?\", \"Monday\")) \n",
+ "print(re.search(r\"Mon(day)?\", \"Mon\")) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 多行匹配"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "None\n",
+ "<_sre.SRE_Match object; span=(18, 19), match='I'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# multi-line\n",
+ "string = \"\"\"\n",
+ "dog runs to cat.\n",
+ "I run to dog.\n",
+ "\"\"\"\n",
+ "print(re.search(r\"^I\", string)) \n",
+ "print(re.search(r\"^I\", string, flags=re.M)) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 0或多次"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(0, 1), match='a'>\n",
+ "<_sre.SRE_Match object; span=(0, 6), match='abbbbb'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# * : occur 0 or more times\n",
+ "print(re.search(r\"ab*\", \"a\")) \n",
+ "print(re.search(r\"ab*\", \"abbbbb\")) \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 1或多次"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "None\n",
+ "<_sre.SRE_Match object; span=(0, 6), match='abbbbb'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# + : occur 1 or more times\n",
+ "print(re.search(r\"ab+\", \"a\")) \n",
+ "print(re.search(r\"ab+\", \"abbbbb\")) \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 可选次数"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "None\n",
+ "<_sre.SRE_Match object; span=(0, 6), match='abbbbb'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# {n, m} : occur n to m times\n",
+ "print(re.search(r\"ab{2,10}\", \"a\")) \n",
+ "print(re.search(r\"ab{2,10}\", \"abbbbb\")) \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## group 组"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "021523, Date: Feb/12/2017\n",
+ "021523\n",
+ "Feb/12/2017\n"
+ ]
+ }
+ ],
+ "source": [
+ "# group\n",
+ "match = re.search(r\"(\\d+), Date: (.+)\", \"ID: 021523, Date: Feb/12/2017\")\n",
+ "print(match.group()) \n",
+ "print(match.group(1)) \n",
+ "print(match.group(2)) "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "021523\n",
+ "Feb/12/2017\n"
+ ]
+ }
+ ],
+ "source": [
+ "match = re.search(r\"(?P\\d+), Date: (?P.+)\", \"ID: 021523, Date: Feb/12/2017\")\n",
+ "print(match.group('id')) \n",
+ "print(match.group('date')) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 寻找所有匹配 "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "['run', 'ran']\n"
+ ]
+ }
+ ],
+ "source": [
+ "# findall\n",
+ "print(re.findall(r\"r[ua]n\", \"run ran ren\")) "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "['run', 'ran']\n"
+ ]
+ }
+ ],
+ "source": [
+ "# | : or\n",
+ "print(re.findall(r\"(run|ran)\", \"run ran ren\")) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 替换"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 22,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "dog catches to cat\n"
+ ]
+ }
+ ],
+ "source": [
+ "# re.sub() replace\n",
+ "print(re.sub(r\"r[au]ns\", \"catches\", \"dog runs to cat\")) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 分裂"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 23,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "['a', 'b', 'c', 'd', 'e']\n"
+ ]
+ }
+ ],
+ "source": [
+ "# re.split()\n",
+ "print(re.split(r\"[,;\\.]\", \"a;b,c.d;e\")) \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## compile"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 24,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<_sre.SRE_Match object; span=(4, 7), match='ran'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "# compile\n",
+ "compiled_re = re.compile(r\"r[ua]n\")\n",
+ "print(compiled_re.search(\"dog ran to cat\")) "
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.5.1"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/kerasTUT/10-save.py b/kerasTUT/10-save.py
index 8838296..ff2670f 100644
--- a/kerasTUT/10-save.py
+++ b/kerasTUT/10-save.py
@@ -1,6 +1,6 @@
"""
To know more or get code samples, please visit my website:
-https://morvanzhou.github.io/tutorials/
+https://mofanpy.com/tutorials/
Or search: 莫烦Python
Thank you for supporting!
"""
diff --git a/kerasTUT/2-installation.py b/kerasTUT/2-installation.py
index 7c8c921..51765ef 100644
--- a/kerasTUT/2-installation.py
+++ b/kerasTUT/2-installation.py
@@ -1,6 +1,6 @@
"""
To know more or get code samples, please visit my website:
-https://morvanzhou.github.io/tutorials/
+https://mofanpy.com/tutorials/
Or search: 莫烦Python
Thank you for supporting!
"""
diff --git a/kerasTUT/3-backend.py b/kerasTUT/3-backend.py
index 93a68e9..8e7ee00 100644
--- a/kerasTUT/3-backend.py
+++ b/kerasTUT/3-backend.py
@@ -1,6 +1,6 @@
"""
To know more or get code samples, please visit my website:
-https://morvanzhou.github.io/tutorials/
+https://mofanpy.com/tutorials/
Or search: 莫烦Python
Thank you for supporting!
"""
diff --git a/kerasTUT/4-regressor_example.py b/kerasTUT/4-regressor_example.py
index e41e2ad..2af1e03 100644
--- a/kerasTUT/4-regressor_example.py
+++ b/kerasTUT/4-regressor_example.py
@@ -1,6 +1,6 @@
"""
To know more or get code samples, please visit my website:
-https://morvanzhou.github.io/tutorials/
+https://mofanpy.com/tutorials/
Or search: 莫烦Python
Thank you for supporting!
"""
diff --git a/kerasTUT/5-classifier_example.py b/kerasTUT/5-classifier_example.py
index 20cecb3..9e744c6 100644
--- a/kerasTUT/5-classifier_example.py
+++ b/kerasTUT/5-classifier_example.py
@@ -1,6 +1,6 @@
"""
To know more or get code samples, please visit my website:
-https://morvanzhou.github.io/tutorials/
+https://mofanpy.com/tutorials/
Or search: 莫烦Python
Thank you for supporting!
"""
diff --git a/kerasTUT/6-CNN_example.py b/kerasTUT/6-CNN_example.py
index 05ff0bc..eda3ec8 100644
--- a/kerasTUT/6-CNN_example.py
+++ b/kerasTUT/6-CNN_example.py
@@ -1,6 +1,6 @@
"""
To know more or get code samples, please visit my website:
-https://morvanzhou.github.io/tutorials/
+https://mofanpy.com/tutorials/
Or search: 莫烦Python
Thank you for supporting!
"""
@@ -23,7 +23,7 @@
from keras.optimizers import Adam
# download the mnist to the path '~/.keras/datasets/' if it is the first time to be called
-# X shape (60,000 28x28), y shape (10,000, )
+# training X shape (60000, 28x28), Y shape (60000, ). test X shape (10000, 28x28), Y shape (10000, )
(X_train, y_train), (X_test, y_test) = mnist.load_data()
# data pre-processing
@@ -37,7 +37,7 @@
# Conv layer 1 output shape (32, 28, 28)
model.add(Convolution2D(
- batch_input_shape=(64, 1, 28, 28),
+ batch_input_shape=(None, 1, 28, 28),
filters=32,
kernel_size=5,
strides=1,
diff --git a/kerasTUT/7-RNN_Classifier_example.py b/kerasTUT/7-RNN_Classifier_example.py
index 92001df..368c357 100644
--- a/kerasTUT/7-RNN_Classifier_example.py
+++ b/kerasTUT/7-RNN_Classifier_example.py
@@ -1,6 +1,6 @@
"""
To know more or get code samples, please visit my website:
-https://morvanzhou.github.io/tutorials/
+https://mofanpy.com/tutorials/
Or search: 莫烦Python
Thank you for supporting!
"""
diff --git a/kerasTUT/8-RNN_LSTM_Regressor_example.py b/kerasTUT/8-RNN_LSTM_Regressor_example.py
index 0b6581d..83aee5e 100644
--- a/kerasTUT/8-RNN_LSTM_Regressor_example.py
+++ b/kerasTUT/8-RNN_LSTM_Regressor_example.py
@@ -1,6 +1,6 @@
"""
To know more or get code samples, please visit my website:
-https://morvanzhou.github.io/tutorials/
+https://mofanpy.com/tutorials/
Or search: 莫烦Python
Thank you for supporting!
"""
diff --git a/kerasTUT/9-Autoencoder_example.py b/kerasTUT/9-Autoencoder_example.py
index 2cf8cce..754c2bd 100644
--- a/kerasTUT/9-Autoencoder_example.py
+++ b/kerasTUT/9-Autoencoder_example.py
@@ -1,6 +1,6 @@
"""
To know more or get code samples, please visit my website:
-https://morvanzhou.github.io/tutorials/
+https://mofanpy.com/tutorials/
Or search: 莫烦Python
Thank you for supporting!
"""
diff --git a/kerasTUT/README.md b/kerasTUT/README.md
index 55f37c4..0427e98 100644
--- a/kerasTUT/README.md
+++ b/kerasTUT/README.md
@@ -2,19 +2,19 @@
In these tutorials for Tensorflow, we will build our first Neural Network and try to build some advanced Neural Network architectures developed recent years.
-All methods mentioned below have their video and text tutorial in Chinese. Visit [莫烦 Python](https://morvanzhou.github.io/tutorials/) for more.
+All methods mentioned below have their video and text tutorial in Chinese. Visit [莫烦 Python](https://mofanpy.com/) for more.
If you speak Chinese, you can watch my [Youtube channel](https://www.youtube.com/channel/UCdyjiB5H8Pu7aDTNVXTTpcg) as well.
-* [Install](https://github.com/MorvanZhou/tutorials/blob/master/kerasTUT/2-installation.py)
-* [Backend (Tensorflow/Theano)](https://github.com/MorvanZhou/tutorials/blob/master/kerasTUT/3-backend.py)
+* [Install](2-installation.py)
+* [Backend (Tensorflow/Theano)](3-backend.py)
* Networks
- * [Simple Regressor](https://github.com/MorvanZhou/tutorials/blob/master/kerasTUT/4-regressor_example.py)
- * [Simple Classifier](https://github.com/MorvanZhou/tutorials/blob/master/kerasTUT/5-classifier_example.py)
- * [CNN](https://github.com/MorvanZhou/tutorials/blob/master/kerasTUT/6-CNN_example.py)
- * [RNN classifier](https://github.com/MorvanZhou/tutorials/blob/master/kerasTUT/7-RNN_Classifier_example.py)
- * [RNN LSTM regressor](https://github.com/MorvanZhou/tutorials/blob/master/kerasTUT/8-RNN_LSTM_Regressor_example.py)
- * [Autoencoder](https://github.com/MorvanZhou/tutorials/blob/master/kerasTUT/9-Autoencoder_example.py)
+ * [Simple Regressor](4-regressor_example.py)
+ * [Simple Classifier](5-classifier_example.py)
+ * [CNN](6-CNN_example.py)
+ * [RNN classifier](7-RNN_Classifier_example.py)
+ * [RNN LSTM regressor](8-RNN_LSTM_Regressor_example.py)
+ * [Autoencoder](9-Autoencoder_example.py)
# Donation
@@ -31,7 +31,7 @@ If you speak Chinese, you can watch my [Youtube channel](https://www.youtube.com
\ No newline at end of file
diff --git a/matplotlibTUT/README.md b/matplotlibTUT/README.md
index b260de2..5dbf09e 100644
--- a/matplotlibTUT/README.md
+++ b/matplotlibTUT/README.md
@@ -1,50 +1,50 @@
# Python Matplotlib methods and tutorials
-All methods mentioned below have their video and text tutorial in Chinese. Visit [莫烦 Python](https://morvanzhou.github.io/tutorials/) for more.
+All methods mentioned below have their video and text tutorial in Chinese. Visit [莫烦 Python](https://mofanpy.com/tutorials/) for more.
-* [Install](https://github.com/MorvanZhou/tutorials/blob/master/matplotlibTUT/plt2_install.py)
-* [Basic usage](https://github.com/MorvanZhou/tutorials/blob/master/matplotlibTUT/plt3_simple_plot.py)
- * [Figure](https://github.com/MorvanZhou/tutorials/blob/master/matplotlibTUT/plt4_figure.py)
- * [Axis setting1](https://github.com/MorvanZhou/tutorials/blob/master/matplotlibTUT/plt5_ax_setting1.py)
- * [Axis setting2](https://github.com/MorvanZhou/tutorials/blob/master/matplotlibTUT/plt6_ax_setting2.py)
- * [Legend](https://github.com/MorvanZhou/tutorials/blob/master/matplotlibTUT/plt7_legend.py)
- * [Annotation](https://github.com/MorvanZhou/tutorials/blob/master/matplotlibTUT/plt8_annotation.py)
- * [Deal with Tick](https://github.com/MorvanZhou/tutorials/blob/master/matplotlibTUT/plt9_tick_visibility.py)
+* [Install](plt2_install.py)
+* [Basic usage](plt3_simple_plot.py)
+ * [Figure](plt4_figure.py)
+ * [Axis setting1](plt5_ax_setting1.py)
+ * [Axis setting2](plt6_ax_setting2.py)
+ * [Legend](plt7_legend.py)
+ * [Annotation](plt8_annotation.py)
+ * [Deal with Tick](plt9_tick_visibility.py)
* Drawing
- * [Scatter](https://github.com/MorvanZhou/tutorials/blob/master/matplotlibTUT/plt10_scatter.py)
- * [Bar](https://github.com/MorvanZhou/tutorials/blob/master/matplotlibTUT/plt11_bar.py)
- * [Contours](https://github.com/MorvanZhou/tutorials/blob/master/matplotlibTUT/plt12_contours.py)
- * [Image](https://github.com/MorvanZhou/tutorials/blob/master/matplotlibTUT/plt13_image.py)
- * [3D plot](https://github.com/MorvanZhou/tutorials/blob/master/matplotlibTUT/plt14_3d.py)
+ * [Scatter](plt10_scatter.py)
+ * [Bar](plt11_bar.py)
+ * [Contours](plt12_contours.py)
+ * [Image](plt13_image.py)
+ * [3D plot](plt14_3d.py)
* Subplots
- * [Subplot1](https://github.com/MorvanZhou/tutorials/blob/master/matplotlibTUT/plt15_subplot.py)
- * [Grid Subplot](https://github.com/MorvanZhou/tutorials/blob/master/matplotlibTUT/plt16_grid_subplot.py)
- * [Plot in Plot](https://github.com/MorvanZhou/tutorials/blob/master/matplotlibTUT/plt17_plot_in_plot.py)
- * [Second y-axis](https://github.com/MorvanZhou/tutorials/blob/master/matplotlibTUT/plt18_secondary_yaxis.py)
+ * [Subplot1](plt15_subplot.py)
+ * [Grid Subplot](plt16_grid_subplot.py)
+ * [Plot in Plot](plt17_plot_in_plot.py)
+ * [Second y-axis](plt18_secondary_yaxis.py)
* Animation
- * [Function Animation](https://github.com/MorvanZhou/tutorials/blob/master/matplotlibTUT/plt19_animation.py)
+ * [Function Animation](plt19_animation.py)
# Some plots from these tutorials:
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
# Donation
@@ -60,7 +60,7 @@ All methods mentioned below have their video and text tutorial in Chinese. Visit
\ No newline at end of file
diff --git a/matplotlibTUT/plt7_legend.py b/matplotlibTUT/plt7_legend.py
index 40051ca..1f690c3 100644
--- a/matplotlibTUT/plt7_legend.py
+++ b/matplotlibTUT/plt7_legend.py
@@ -30,11 +30,11 @@
plt.yticks([-2, -1.8, -1, 1.22, 3],
[r'$really\ bad$', r'$bad$', r'$normal$', r'$good$', r'$really\ good$'])
-l1, = plt.plot(x, y2, label='linear line')
-l2, = plt.plot(x, y1, color='red', linewidth=1.0, linestyle='--', label='square line')
+l1, = plt.plot(x, y1, label='linear line')
+l2, = plt.plot(x, y2, color='red', linewidth=1.0, linestyle='--', label='square line')
-# plt.legend(loc='upper right')
-plt.legend(handles=[l1, l2], labels=['up', 'down'], loc='best')
+plt.legend(loc='upper right')
+# plt.legend(handles=[l1, l2], labels=['up', 'down'], loc='best')
# the "," is very important in here l1, = plt... and l2, = plt... for this step
"""legend( handles=(line1, line2, line3),
labels=('label1', 'label2', 'label3'),
diff --git a/matplotlibTUT/plt9_tick_visibility.py b/matplotlibTUT/plt9_tick_visibility.py
index c0ec70e..a43fffd 100644
--- a/matplotlibTUT/plt9_tick_visibility.py
+++ b/matplotlibTUT/plt9_tick_visibility.py
@@ -18,7 +18,7 @@
y = 0.1*x
plt.figure()
-plt.plot(x, y, linewidth=10)
+plt.plot(x, y, linewidth=10, zorder=1) # set zorder for ordering the plot in plt 2.0.2 or higher
plt.ylim(-2, 2)
ax = plt.gca()
ax.spines['right'].set_color('none')
@@ -32,5 +32,6 @@
for label in ax.get_xticklabels() + ax.get_yticklabels():
label.set_fontsize(12)
- label.set_bbox(dict(facecolor='white', edgecolor='None', alpha=0.7))
+ # set zorder for ordering the plot in plt 2.0.2 or higher
+ label.set_bbox(dict(facecolor='white', edgecolor='none', alpha=0.8, zorder=2))
plt.show()
diff --git a/pyTorch tutorial/README.md b/pyTorch tutorial/README.md
index b26a2ce..660a0c8 100644
--- a/pyTorch tutorial/README.md
+++ b/pyTorch tutorial/README.md
@@ -1,6 +1,6 @@
- 
+ 
@@ -10,11 +10,11 @@
# This pyTorch Tutorial has been moved to anther independent repo:
-[https://github.com/MorvanZhou/PyTorch-Tutorial](https://github.com/MorvanZhou/PyTorch-Tutorial)
+[/MorvanZhou/PyTorch-Tutorial](/MorvanZhou/PyTorch-Tutorial)
# 请注意, 这个 PyTorch 的教程代码已经被移至另一个网页:
-[https://github.com/MorvanZhou/PyTorch-Tutorial](https://github.com/MorvanZhou/PyTorch-Tutorial)
+[/MorvanZhou/PyTorch-Tutorial](/MorvanZhou/PyTorch-Tutorial)
# Donation
@@ -31,7 +31,7 @@
diff --git a/tensorflowTUT/README.md b/tensorflowTUT/README.md
index 934e55a..2637277 100644
--- a/tensorflowTUT/README.md
+++ b/tensorflowTUT/README.md
@@ -1,6 +1,6 @@
- 
+ 
@@ -14,38 +14,38 @@
In these tutorials for Tensorflow, we will build our first Neural Network and try to build some advanced Neural Network architectures developed recent years.
-All methods mentioned below have their video and text tutorial in Chinese. Visit [莫烦 Python](https://morvanzhou.github.io/tutorials/) for more.
+All methods mentioned below have their video and text tutorial in Chinese. Visit [莫烦 Python](https://mofanpy.com/tutorials/) for more.
If you speak Chinese, you can watch my [Youtube channel](https://www.youtube.com/channel/UCdyjiB5H8Pu7aDTNVXTTpcg) as well.
**As many requests about making these tutorials available in English, please find them in this playlist:** ([https://www.youtube.com/playlist?list=PLXO45tsB95cJHXaDKpbwr5fC_CCYylw1f](https://www.youtube.com/playlist?list=PLXO45tsB95cJHXaDKpbwr5fC_CCYylw1f))
* Tensorflow Basic
- * [Basic example](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tf5_example2/full_code.py)
- * [Session](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tensorflow6_session.py)
- * [Variable](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tensorflow7_variable.py)
- * [Placeholder](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tensorflow8_feeds.py)
+ * [Basic example](tf5_example2/full_code.py)
+ * [Session](tensorflow6_session.py)
+ * [Variable](tensorflow7_variable.py)
+ * [Placeholder](tensorflow8_feeds.py)
* Build your first NN
- * [Adding layer](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tensorflow10_def_add_layer.py)
- * [Build NN](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tf11_build_network/full_code.py)
- * [Visualize update](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tf12_plot_result/full_code.py)
+ * [Adding layer](tensorflow10_def_add_layer.py)
+ * [Build NN](tf11_build_network/full_code.py)
+ * [Visualize update](tf12_plot_result/full_code.py)
* Tensorboard
- * [Visualization 1](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tf14_tensorboard/full_code.py)
- * [Visualization 2](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tf15_tensorboard/full_code.py)
-* [Classification](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tf16_classification/full_code.py)
-* [Overfitting and dropout](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tf17_dropout/full_code.py)
-* [Save Network](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tf19_saver.py)
+ * [Visualization 1](tf14_tensorboard/full_code.py)
+ * [Visualization 2](tf15_tensorboard/full_code.py)
+* [Classification](tf16_classification/full_code.py)
+* [Overfitting and dropout](tf17_dropout/full_code.py)
+* [Save Network](tf19_saver.py)
* CNN
- * [CNN layers](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tf18_CNN2/full_code.py)
- * [CNN training](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tf18_CNN3/full_code.py)
+ * [CNN layers](tf18_CNN2/full_code.py)
+ * [CNN training](tf18_CNN3/full_code.py)
* RNN
- * [Classification](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tf20_RNN2/full_code.py)
- * [Regression](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tf20_RNN2.2/full_code.py)
-* [Autoencoder](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tf21_autoencoder/full_code.py)
+ * [Classification](tf20_RNN2/full_code.py)
+ * [Regression](tf20_RNN2.2/full_code.py)
+* [Autoencoder](tf21_autoencoder/full_code.py)
* Scope
- * [Scope in TF](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tf22_scope/tf22_scope.py)
- * [Training Testing for RNN](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tf22_scope/tf22_RNN_scope.py)
-* [Batch Normalization](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tf23_BN/tf23_BN.py)
+ * [Scope in TF](tf22_scope/tf22_scope.py)
+ * [Training Testing for RNN](tf22_scope/tf22_RNN_scope.py)
+* [Batch Normalization](tf23_BN/tf23_BN.py)
@@ -63,7 +63,7 @@ If you speak Chinese, you can watch my [Youtube channel](https://www.youtube.com
diff --git a/tensorflowTUT/tf15_tensorboard/logs/events.out.tfevents.1494075549.Morvan b/tensorflowTUT/tf15_tensorboard/logs/events.out.tfevents.1494075549.Morvan
new file mode 100644
index 0000000..561ea24
Binary files /dev/null and b/tensorflowTUT/tf15_tensorboard/logs/events.out.tfevents.1494075549.Morvan differ
diff --git a/tensorflowTUT/tf20_RNN2.2/full_code.py b/tensorflowTUT/tf20_RNN2.2/full_code.py
index 6e1b4bc..7157bb7 100644
--- a/tensorflowTUT/tf20_RNN2.2/full_code.py
+++ b/tensorflowTUT/tf20_RNN2.2/full_code.py
@@ -100,7 +100,8 @@ def compute_cost(self):
name='average_cost')
tf.summary.scalar('cost', self.cost)
- def ms_error(self, labels, logits):
+ @staticmethod
+ def ms_error(labels, logits):
return tf.square(tf.subtract(labels, logits))
def _weight_variable(self, shape, name='weights'):
diff --git a/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1490697566.Morvan b/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1490697566.Morvan
new file mode 100644
index 0000000..f00f316
Binary files /dev/null and b/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1490697566.Morvan differ
diff --git a/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1490697588.Morvan b/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1490697588.Morvan
new file mode 100644
index 0000000..b2499d1
Binary files /dev/null and b/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1490697588.Morvan differ
diff --git a/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1493818356.Morvan b/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1493818356.Morvan
new file mode 100644
index 0000000..8ac8cb2
Binary files /dev/null and b/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1493818356.Morvan differ
diff --git a/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1493818411.Morvan b/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1493818411.Morvan
new file mode 100644
index 0000000..13dd514
Binary files /dev/null and b/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1493818411.Morvan differ
diff --git a/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1493818762.Morvan b/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1493818762.Morvan
new file mode 100644
index 0000000..e790ee0
Binary files /dev/null and b/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1493818762.Morvan differ
diff --git a/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1509756112.Morvan b/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1509756112.Morvan
new file mode 100644
index 0000000..7b9ae16
Binary files /dev/null and b/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1509756112.Morvan differ
diff --git a/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1509756156.Morvan b/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1509756156.Morvan
new file mode 100644
index 0000000..6988176
Binary files /dev/null and b/tensorflowTUT/tf20_RNN2.2/logs/events.out.tfevents.1509756156.Morvan differ
diff --git a/tensorflowTUT/tf20_RNN2/MNIST_data/t10k-images-idx3-ubyte.gz b/tensorflowTUT/tf20_RNN2/MNIST_data/t10k-images-idx3-ubyte.gz
new file mode 100644
index 0000000..5ace8ea
Binary files /dev/null and b/tensorflowTUT/tf20_RNN2/MNIST_data/t10k-images-idx3-ubyte.gz differ
diff --git a/tensorflowTUT/tf20_RNN2/MNIST_data/t10k-labels-idx1-ubyte.gz b/tensorflowTUT/tf20_RNN2/MNIST_data/t10k-labels-idx1-ubyte.gz
new file mode 100644
index 0000000..a7e1415
Binary files /dev/null and b/tensorflowTUT/tf20_RNN2/MNIST_data/t10k-labels-idx1-ubyte.gz differ
diff --git a/tensorflowTUT/tf20_RNN2/MNIST_data/train-images-idx3-ubyte.gz b/tensorflowTUT/tf20_RNN2/MNIST_data/train-images-idx3-ubyte.gz
new file mode 100644
index 0000000..b50e4b6
Binary files /dev/null and b/tensorflowTUT/tf20_RNN2/MNIST_data/train-images-idx3-ubyte.gz differ
diff --git a/tensorflowTUT/tf20_RNN2/MNIST_data/train-labels-idx1-ubyte.gz b/tensorflowTUT/tf20_RNN2/MNIST_data/train-labels-idx1-ubyte.gz
new file mode 100644
index 0000000..707a576
Binary files /dev/null and b/tensorflowTUT/tf20_RNN2/MNIST_data/train-labels-idx1-ubyte.gz differ
diff --git a/tensorflowTUT/tf21_autoencoder/full_code.py b/tensorflowTUT/tf21_autoencoder/full_code.py
index 4705b23..10097ce 100644
--- a/tensorflowTUT/tf21_autoencoder/full_code.py
+++ b/tensorflowTUT/tf21_autoencoder/full_code.py
@@ -1,6 +1,6 @@
# View more python learning tutorial on my Youtube and Youku channel!!!
-# My tutorial website: https://morvanzhou.github.io/tutorials/
+# My tutorial website: https://mofanpy.com/tutorials/
from __future__ import division, print_function, absolute_import
diff --git a/tensorflowTUT/tf22_scope/tf22_RNN_scope.py b/tensorflowTUT/tf22_scope/tf22_RNN_scope.py
index d816b48..15715c9 100644
--- a/tensorflowTUT/tf22_scope/tf22_RNN_scope.py
+++ b/tensorflowTUT/tf22_scope/tf22_RNN_scope.py
@@ -1,4 +1,4 @@
-# visit https://morvanzhou.github.io/tutorials/ for more!
+# visit https://mofanpy.com/tutorials/ for more!
# 22 scope (name_scope/variable_scope)
diff --git a/tensorflowTUT/tf22_scope/tf22_scope.py b/tensorflowTUT/tf22_scope/tf22_scope.py
index 0906957..c7972b0 100644
--- a/tensorflowTUT/tf22_scope/tf22_scope.py
+++ b/tensorflowTUT/tf22_scope/tf22_scope.py
@@ -1,4 +1,4 @@
-# visit https://morvanzhou.github.io/tutorials/ for more!
+# visit https://mofanpy.com/tutorials/ for more!
# 22 scope (name_scope/variable_scope)
diff --git a/tensorflowTUT/tf23_BN/tf23_BN.py b/tensorflowTUT/tf23_BN/tf23_BN.py
index 592462b..bb46188 100644
--- a/tensorflowTUT/tf23_BN/tf23_BN.py
+++ b/tensorflowTUT/tf23_BN/tf23_BN.py
@@ -1,5 +1,5 @@
"""
-visit https://morvanzhou.github.io/tutorials/ for more!
+visit https://mofanpy.com/tutorials/ for more!
Build two networks.
1. Without batch normalization
diff --git a/tensorflowTUT/tf5_example2/full_code.py b/tensorflowTUT/tf5_example2/full_code.py
index 4a857be..6b1a9ee 100644
--- a/tensorflowTUT/tf5_example2/full_code.py
+++ b/tensorflowTUT/tf5_example2/full_code.py
@@ -23,8 +23,6 @@
loss = tf.reduce_mean(tf.square(y-y_data))
optimizer = tf.train.GradientDescentOptimizer(0.5)
train = optimizer.minimize(loss)
-
-init = tf.initialize_all_variables()
### create tensorflow structure end ###
sess = tf.Session()
diff --git a/theanoTUT/README.md b/theanoTUT/README.md
index cc4161f..18c4c6d 100644
--- a/theanoTUT/README.md
+++ b/theanoTUT/README.md
@@ -1,22 +1,22 @@
# Python Theano methods and tutorials
-All methods mentioned below have their video and text tutorial in Chinese. Visit [莫烦 Python](https://morvanzhou.github.io/tutorials/) for more.
+All methods mentioned below have their video and text tutorial in Chinese. Visit [莫烦 Python](https://mofanpy.com/tutorials/) for more.
-* [Install](https://github.com/MorvanZhou/tutorials/blob/master/theanoTUT/theano2_install.py)
-* [Example of Machine Learning](https://github.com/MorvanZhou/tutorials/blob/master/theanoTUT/theano3_what_does_ML_do.py)
+* [Install](theano2_install.py)
+* [Example of Machine Learning](theano3_what_does_ML_do.py)
* Basic
- * [Basic Usage](https://github.com/MorvanZhou/tutorials/blob/master/theanoTUT/theano4_basic_usage.py)
- * [Function](https://github.com/MorvanZhou/tutorials/blob/master/theanoTUT/theano5_function.py)
- * [Shared Variable](https://github.com/MorvanZhou/tutorials/blob/master/theanoTUT/theano6_shared_variable.py)
- * [Activation Function](https://github.com/MorvanZhou/tutorials/blob/master/theanoTUT/theano7_activation_function.py)
+ * [Basic Usage](theano4_basic_usage.py)
+ * [Function](theano5_function.py)
+ * [Shared Variable](theano6_shared_variable.py)
+ * [Activation Function](theano7_activation_function.py)
* Build a Network
- * [Layer](https://github.com/MorvanZhou/tutorials/blob/master/theanoTUT/theano8_Layer_class.py)
- * [Regression](https://github.com/MorvanZhou/tutorials/blob/master/theanoTUT/theano9_regression_nn/full_code.py)
- * [Visualize Regression](https://github.com/MorvanZhou/tutorials/blob/master/theanoTUT/theano10_regression_visualization/full_code.py)
- * [Classification](https://github.com/MorvanZhou/tutorials/blob/master/theanoTUT/theano11_classification_nn/full_code.py)
- * [Regularization](https://github.com/MorvanZhou/tutorials/tree/master/theanoTUT/theano12_regularization)
- * [Save model](https://github.com/MorvanZhou/tutorials/blob/master/theanoTUT/theano13_save/full_code.py)
+ * [Layer](theano8_Layer_class.py)
+ * [Regression](theano9_regression_nn/full_code.py)
+ * [Visualize Regression](theano10_regression_visualization/full_code.py)
+ * [Classification](theano11_classification_nn/full_code.py)
+ * [Regularization](https://github.com/MorvanZhou/tutorials/tree/master/theano12_regularization)
+ * [Save model](theano13_save/full_code.py)
# Donation
@@ -32,7 +32,7 @@ All methods mentioned below have their video and text tutorial in Chinese. Visit
\ No newline at end of file
diff --git a/tkinterTUT/ins.gif b/tkinterTUT/ins.gif
new file mode 100644
index 0000000..76ad3be
Binary files /dev/null and b/tkinterTUT/ins.gif differ
diff --git a/tkinterTUT/tk11_msgbox.py b/tkinterTUT/tk11_msgbox.py
index 10f4441..bf54615 100644
--- a/tkinterTUT/tk11_msgbox.py
+++ b/tkinterTUT/tk11_msgbox.py
@@ -4,15 +4,16 @@
# Youku video tutorial: http://i.youku.com/pythontutorial
import tkinter as tk
+import tkinter.messagebox
window = tk.Tk()
window.title('my window')
window.geometry('200x200')
def hit_me():
- #tk.messagebox.showinfo(title='Hi', message='hahahaha')
- #tk.messagebox.showwarning(title='Hi', message='nononono')
- #tk.messagebox.showerror(title='Hi', message='No!! never')
+ #tk.messagebox.showinfo(title='Hi', message='hahahaha') # return 'ok'
+ #tk.messagebox.showwarning(title='Hi', message='nononono') # return 'ok'
+ #tk.messagebox.showerror(title='Hi', message='No!! never') # return 'ok'
#print(tk.messagebox.askquestion(title='Hi', message='hahahaha')) # return 'yes' , 'no'
#print(tk.messagebox.askyesno(title='Hi', message='hahahaha')) # return True, False
print(tk.messagebox.asktrycancel(title='Hi', message='hahahaha')) # return True, False
