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Public Library data mining project, using classification algorithms to place new books in collections.
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charleszange/DataMining_CourseProject
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Charles Zange README - INFO634 final Updated 6/9/2019 06:17PM DATA SOURCE Public Domain data from Seattle Public Library as published on Kaggle: https://www.kaggle.com/datasets/city-of-seattle/seattle-library-collection-inventory The license I apply to this work is related to my code and writing only - the data are listed as Public Domain through the Kaggle link above. ************************ SECTIONS 1 Package details 2 How to run code ****1**** Package details -------------- Package includes the following files: - Zange_634Final_Code.ipynb - iPython file containing final version of code - /.ipynb_checkpoints - directory of supporting files for the iPython file - Zange_634Final_Paper.pdf - the final paper summarizing the entire project - Zange_634Final_README.txt - this document For further details on the data and this project, please consult Zange_634Final_Paper ****2**** How to run code -------------- To run the code, you will need a iPython environment like Jupyter Lab or equivalent. Jupyter lab is included in the Anaconda distribution of Python. Python 3 is used for this project. For more details on resources used for this project, please consult Zange_634Final_Paper, specifically the Resources section. Once you have a Jupyter Lab environment open within the project directory, open the Zange_634Final_Code.ipynb to see fully executed code. Outputs are already included in the iPython blocks, so running of the code is not needed to view completed status. If rerunning becomes necessary, you may restart the kernel and rerun all outputs using the Kernel dropdown menu at the top of the window.
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