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lijin-THUlijin-THU
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添加了新的部分11.04-06，新的参考资料，添加了小部分内容
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‎04. scipy/04.01 scienticfic python overview.ipynb

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‎05. advanced python/05.02 interacting with the OS - os.ipynb

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‎09. theano/09.15 tensor module.ipynb

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Theano 张量 tensor 模块 "
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"# Theano tensor 模块 "
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]
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},
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{

‎11. useful tools/11.04 glob.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# glob 模块：文件模式匹配"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"import glob"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"`glob` 模块提供了方便的文件模式匹配方法。\n",
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"\n",
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"例如，找到所有以 `.ipynb` 结尾的文件名："
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"['11.03 json.ipynb',\n",
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" '11.01 pprint.ipynb',\n",
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" '11.02 pickle and cpickle.ipynb',\n",
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" '11.04 glob.ipynb']"
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]
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},
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"glob.glob(\"*.ipynb\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"`glob` 函数支持三种格式的语法：\n",
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"\n",
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"- `*` 匹配单个或多个字符\n",
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"- `?` 匹配任意单个字符\n",
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"- `[]` 匹配指定范围内的字符，如：[0-9]匹配数字。\n",
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"\n",
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"假设我们要匹配第 09 节所有的 `.ipynb` 文件："
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"['../09. theano/09.05 configuration settings and compiling modes.ipynb',\n",
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" '../09. theano/09.03 gpu on windows.ipynb',\n",
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" '../09. theano/09.07 loop with scan.ipynb',\n",
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" '../09. theano/09.13 modern net on mnist.ipynb',\n",
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" '../09. theano/09.11 net on mnist.ipynb',\n",
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" '../09. theano/09.09 logistic regression .ipynb',\n",
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" '../09. theano/09.10 softmax on mnist.ipynb',\n",
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" '../09. theano/09.01 introduction and installation.ipynb',\n",
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" '../09. theano/09.02 theano basics.ipynb',\n",
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" '../09. theano/09.12 random streams.ipynb',\n",
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" '../09. theano/09.04 graph structures.ipynb',\n",
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" '../09. theano/09.14 convolutional net on mnist.ipynb',\n",
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" '../09. theano/09.08 linear regression.ipynb',\n",
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" '../09. theano/09.15 tensor module.ipynb',\n",
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" '../09. theano/09.06 conditions in theano.ipynb']"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"glob.glob(\"../09*/*.ipynb\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"匹配数字开头的文件夹名："
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"['../04. scipy',\n",
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" '../02. python essentials',\n",
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" '../07. interfacing with other languages',\n",
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" '../11. useful tools',\n",
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" '../05. advanced python',\n",
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" '../10. something interesting',\n",
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" '../03. numpy',\n",
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" '../06. matplotlib',\n",
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" '../08. object-oriented programming',\n",
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" '../01. python tools',\n",
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" '../09. theano']"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"glob.glob(\"../[0-9]*\")"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 2",
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"language": "python",
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"name": "python2"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}

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