enar_2019_tutorial
所属分类：数据可视化
开发工具：Jupyter Notebook
文件大小：7228KB
下载次数：0
上传日期：2019-03-26 23:15:30
上 传 者：
sh-1993
说明： 统计编程和数据科学Python入门
(A Primer on Python for Statistical Programming and Data Science)
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# ENAR 2019 Tutorial
## A Primer on Python for Statistical Programming and Data Science
**Christopher Fonnesbeck** Senior Quantitative Analyst, New York Yankees
Though Python is ostensibly a general-purpose programming language, it has quickly become a dominant language for machine learning and data science applications. This is due in part to its fundamental strengths as a high-level language, and in part to the powerful set of third-party packages that comprise the Python “scientific stack”. In this hands-on tutorial, we will first cover the fundamentals of Python programming, including data structures, control flow, functions, and classes, with particular attention paid to aspects of the language that is idiomatic. The second part of the course will comprise a survey of Python libraries that are relevant for modern data analysis, particularly in the context of data science and probabilistic programming. These include: NumPy, SciPy, Jupyter, pandas, dask, scikit-learn, PyMC3, matplotlib, Seaborn, and TensorFlow. Demonstrations will be motivated with real-data examples, using Jupyter notebooks to allow for interaction and experimentation.
[](https://mybinder.org/v2/gh/fonnesbeck/enar_2019_tutorial/master)
## Tutorial Outline
Tuesday, March 26, 1:45 - 3:30PM
- Intro to Python
- Interactive Computing: Jupyter
- Data Processing: pandas
- Machine Learning: scikit-learn
- Bayesian Statistics: PyMC3
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