2.2.packages_required.ipynb

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    "<h1 style='text-align: center;'>Required Python Packages</h1>\n",
    "<h3 style='text-align: center;'>Shouke Wei, Ph.D. Professor</h3>\n",
    "<h4 style='text-align: center;'>Email: shouke.wei@gmail.com</h4>"
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    "## Objective\n",
    "- glance over the required pakcages"
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    "## 1. Modules, Packages and Libraries"
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    "- A Python module: a python file with function(s) and/or class(es) that you can reuse in your code.\n",
    "- A package: like a directory holding subpackages and modules. \n",
    "- A library: a collection of packages. \n",
    "\n",
    "However, the term \"Python library\" is often used interchangeably with “Python package” because packages can also contain modules and other packages (subpackages)."
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    "## 2. Required Packages"
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    "### 7 packages/libraries:\n",
    "\n",
    "- [Jupyter Notbook](https://jupyter.org/)：an open-source web application, where one can create and share documents that contain live code, tables, math equations, visualizations and narrative text.\n",
    "- [NumPy](https://numpy.org/doc/stable/user/whatisnumpy.html)：the fundamental package for scientific computing in Python. It provides a multidimensional array object, and an assortment of routines for fast operations on arrays.\n",
    "- [Pandas](https://pandas.pydata.org/)：a Python package for fast and efficient processing of tabular data, time series, matrix data, etc.\n",
    "- [Matplotlib](https://matplotlib.org/)：a popular and comprehensive open source package to create static, animated, and interactive visualizations in Python."
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    "- [Seaborn](https://seaborn.pydata.org/): a Python data visualization package based on matplotlib. It provides a high-level interface for creating attractive and informative statistical graphics.\n",
    "- [Statsmodels](https://www.statsmodels.org/stable/index.html): a Python package that provides classes and functions for the estimation of many different statistical models, conducting statistical tests, and statistical data exploration.\n",
    "- [Scikit-learn](https://scikit-learn.org/stable/): a Python package for machine learning built on top of SciPy, integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. "
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