sitc/ml21/preprocessing/11_0_Handy.ipynb

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   "source": [
    "# Course Notes for Learning Intelligent Systems"
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    "Department of Telematic Engineering Systems, Universidad Politécnica de Madrid, © Carlos A. Iglesias"
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   "source": [
    "## [Introduction to  Preprocessing](00_Intro_Preprocessing.ipynb)"
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    "#  Handy libraries\n",
    "Libraries that help in several preprocessing tasks.\n",
    "\n",
    "* [datacleaner](11_1_datacleaner.ipynb)\n",
    "* [autoclean](11_3_autoclean.ipynb)"
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    "# References\n",
    "* [Cleaning and Prepping Data with Python for Data Science — Best Practices and Helpful Packages](https://medium.com/@rrfd/cleaning-and-prepping-data-with-python-for-data-science-best-practices-and-helpful-packages-af1edfbe2a3), DeFilippi, 2019, \n",
    "* [Data Preprocessing for Machine learning in Python, GeeksForGeeks](https://www.geeksforgeeks.org/data-preprocessing-machine-learning-python/), A. Sharma, 2018.\n",
    "* [Handy Python Libraries for Formatting and Cleaning Data](https://mode.com/blog/python-data-cleaning-libraries),  M. Bierly, 2016\n"
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   "source": [
    "## Licence\n",
    "The notebook is freely licensed under under the [Creative Commons Attribution Share-Alike license](https://creativecommons.org/licenses/by/2.0/).  \n",
    "\n",
    "© Carlos A. Iglesias, Universidad Politécnica de Madrid."
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