教程目的

教程面向非程序员，或者是面向公司的Data Analyst。目的是使得非职业开发人员，能够快速掌握Python的使用方法。随着基础教程结束，将会以实际的工作过程中，能够通过Python解决的需求问题为主。

Name		Name	Last commit message	Last commit date
Latest commit History 90 Commits
.idea		.idea
.ipynb_checkpoints		.ipynb_checkpoints
__pycache__		__pycache__
archive.ics.uci.edu/ml/machine-learning-databases/iris		archive.ics.uci.edu/ml/machine-learning-databases/iris
csv		csv
docs/txt/168104986		docs/txt/168104986
excel		excel
html		html
image		image
log		log
mycode		mycode
nlpmodel		nlpmodel
output		output
txt		txt
.gitignore		.gitignore
00.1 GIT and PyCharm Introduction.ipynb		00.1 GIT and PyCharm Introduction.ipynb
00.2 project structure Recommendation.ipynb		00.2 project structure Recommendation.ipynb
00.newfeatureforpython3.x.ipynb		00.newfeatureforpython3.x.ipynb
01.Install and basesyntax.ipynb		01.Install and basesyntax.ipynb
02. basic data type.ipynb		02. basic data type.ipynb
03. comment and exception.ipynb		03. comment and exception.ipynb
04. operator.ipynb		04. operator.ipynb
05. condition control.ipynb		05. condition control.ipynb
06. circle statement.ipynb		06. circle statement.ipynb
07. iterandgenerator.ipynb		07. iterandgenerator.ipynb
08. function.ipynb		08. function.ipynb
09. module.ipynb		09. module.ipynb
10. input and output.ipynb		10. input and output.ipynb
11. object-oriented (class).ipynb		11. object-oriented (class).ipynb
12. regex.ipynb		12. regex.ipynb
13. regex (for python).ipynb		13. regex (for python).ipynb
14. regex samples.ipynb		14. regex samples.ipynb
15. HTML Introduction.ipynb		15. HTML Introduction.ipynb
16. Parse HTML by XPATH.ipynb		16. Parse HTML by XPATH.ipynb
17. Parse HTML by Beautiful Soup 4.ipynb		17. Parse HTML by Beautiful Soup 4.ipynb
17.1 Sample_Crawl Tieba Image Files.ipynb		17.1 Sample_Crawl Tieba Image Files.ipynb
18.1 Web Crawler - Selenium入门及使用.ipynb		18.1 Web Crawler - Selenium入门及使用.ipynb
19. Database Operation By Python.ipynb		19. Database Operation By Python.ipynb
20. Data Operation Package_Numpy.ipynb		20. Data Operation Package_Numpy.ipynb
20.1 Data Operation Package_Numpy_Vital Functions.ipynb		20.1 Data Operation Package_Numpy_Vital Functions.ipynb
20.2 Data Operation Package_Numpy_Samples.ipynb		20.2 Data Operation Package_Numpy_Samples.ipynb
21. Data Mining Package_Pandas.ipynb		21. Data Mining Package_Pandas.ipynb
21.1 Data Mining Package_Pandas_Samples.ipynb		21.1 Data Mining Package_Pandas_Samples.ipynb
22. Machine Learning Basic Introduction.ipynb		22. Machine Learning Basic Introduction.ipynb
22.1 Hello World_Machine Learning.ipynb		22.1 Hello World_Machine Learning.ipynb
22.2 手动实现梯度下降.ipynb		22.2 手动实现梯度下降.ipynb
23. NLP Introduction.ipynb		23. NLP Introduction.ipynb
23.1 Flair NLP Package on PyTorch.ipynb		23.1 Flair NLP Package on PyTorch.ipynb
23.2 TextRank Inroduction.ipynb		23.2 TextRank Inroduction.ipynb
23.3 SnowNLP Practice.ipynb		23.3 SnowNLP Practice.ipynb
24. Neural Network Introduction.ipynb		24. Neural Network Introduction.ipynb
24.0.0 手写最简单的神经网络.ipynb		24.0.0 手写最简单的神经网络.ipynb
24.0.1 PyTorch Basic.ipynb		24.0.1 PyTorch Basic.ipynb
24.1 Pytorch Practice_Fashion MNIST.ipynb		24.1 Pytorch Practice_Fashion MNIST.ipynb
24.2 Transformer Practice_Attention is All You Need.ipynb		24.2 Transformer Practice_Attention is All You Need.ipynb
24.3 ImageDataGenerator in Keras.ipynb		24.3 ImageDataGenerator in Keras.ipynb
25. Interesting Python Libiraries.ipynb		25. Interesting Python Libiraries.ipynb
26. 量化投资相关内容.ipynb		26. 量化投资相关内容.ipynb
27. 优秀的资源收集.ipynb		27. 优秀的资源收集.ipynb
all_requirements.txt		all_requirements.txt
applydir.py		applydir.py
fibo.py		fibo.py
install_need_package.py		install_need_package.py
logutil.py		logutil.py
myfile.txt		myfile.txt
readme.md		readme.md
support.py		support.py
using_name.py		using_name.py

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