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db2_for_machine_learning_samples/Db2 Hackathon - Learnware/README.md
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# Db2 Hackathon - Learnware | ||
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Our recent Db2 hackathon demonstrate the versatile powers of Db2 combined with machine learning, web development, and blochaine. Through this hackathon, we had three amazing winners that used our products in intriguing ways that we would like to showcase. One of the three winners was ***Kuro Souza***. Kuro's project was called `Learnware`. This project used open source data in order to predict student performance. The steps below will show how to re-create Kuro's work for you to try out! | ||
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Original Data Files - https://www.kaggle.com/rocki37/open-university-learning-analytics-dataset | ||
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Live Version of Learnware - http://sparge1.fyre.ibm.com:8888/notebooks/notebook/learnware.ipynb | ||
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## Upload Data Files to Db2 | ||
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The first thing we need to do is upload all the data files into your Db2 instance. If you open the `learnware.ipynb`, the names of the tables for each data file is outlined in the `table_names` list. For reference I have outlined them over here as well. | ||
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1. 'STUDENT_INFO' | ||
2. 'ASSESSMENTS' | ||
3. 'COURSES' | ||
4. 'VLE' | ||
5. 'STUDENT_ASSESSMENT' | ||
6. 'STUDENT_REGISTRATION' | ||
7. 'STUDENT_VLE2' | ||
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**Important Note** Make sure you acquire the service credentials for your Db2 instance in order to connect to the database through the notebook | ||
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## Learnware | ||
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Once the data files have been uploaded with the correct table names, we can now use the `learnware.ipynb` notebook to create our model. As you go through the notebook, make sure to replace the `<>` with your own db2 instance service credentials. | ||
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## Special Notes | ||
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Special thanks Kuro Souza for letting us use to Db2 Hackathon project as a way to demonstrate the power the Db2 paired with AI and machine learning! | ||
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Check you this Github repo - https://github.com/kurosouza | ||
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This notebook and project has only been run on Db2 on Cloud Free Tier instance. | ||
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db2_for_machine_learning_samples/Db2 Hackathon - Learnware/data/assessments.csv
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"code_module","code_presentation","id_assessment","assessment_type","date","weight" | ||
"AAA","2013J","1752","TMA","19","10" | ||
"AAA","2013J","1753","TMA","54","20" | ||
"AAA","2013J","1754","TMA","117","20" | ||
"AAA","2013J","1755","TMA","166","20" | ||
"AAA","2013J","1756","TMA","215","30" | ||
"AAA","2013J","1757","Exam","","100" | ||
"AAA","2014J","1758","TMA","19","10" | ||
"AAA","2014J","1759","TMA","54","20" | ||
"AAA","2014J","1760","TMA","117","20" | ||
"AAA","2014J","1761","TMA","166","20" | ||
"AAA","2014J","1762","TMA","215","30" | ||
"AAA","2014J","1763","Exam","","100" | ||
"BBB","2013B","14991","CMA","54","1" | ||
"BBB","2013B","14992","CMA","89","1" | ||
"BBB","2013B","14993","CMA","124","1" | ||
"BBB","2013B","14994","CMA","159","1" | ||
"BBB","2013B","14995","CMA","187","1" | ||
"BBB","2013B","14984","TMA","19","5" | ||
"BBB","2013B","14985","TMA","47","18" | ||
"BBB","2013B","14986","TMA","89","18" | ||
"BBB","2013B","14987","TMA","124","18" | ||
"BBB","2013B","14988","TMA","159","18" | ||
"BBB","2013B","14989","TMA","187","18" | ||
"BBB","2013B","14990","Exam","","100" | ||
"BBB","2013J","15003","CMA","54","1" | ||
"BBB","2013J","15004","CMA","96","1" | ||
"BBB","2013J","15005","CMA","131","1" | ||
"BBB","2013J","15006","CMA","166","1" | ||
"BBB","2013J","15007","CMA","208","1" | ||
"BBB","2013J","14996","TMA","19","5" | ||
"BBB","2013J","14997","TMA","47","18" | ||
"BBB","2013J","14998","TMA","96","18" | ||
"BBB","2013J","14999","TMA","131","18" | ||
"BBB","2013J","15000","TMA","166","18" | ||
"BBB","2013J","15001","TMA","208","18" | ||
"BBB","2013J","15002","Exam","","100" | ||
"BBB","2014B","15015","CMA","47","1" | ||
"BBB","2014B","15016","CMA","82","1" | ||
"BBB","2014B","15017","CMA","117","1" | ||
"BBB","2014B","15018","CMA","152","1" | ||
"BBB","2014B","15019","CMA","194","1" | ||
"BBB","2014B","15008","TMA","12","5" | ||
"BBB","2014B","15009","TMA","40","18" | ||
"BBB","2014B","15010","TMA","82","18" | ||
"BBB","2014B","15011","TMA","117","18" | ||
"BBB","2014B","15012","TMA","152","18" | ||
"BBB","2014B","15013","TMA","194","18" | ||
"BBB","2014B","15014","Exam","","100" | ||
"BBB","2014J","15020","TMA","19","0" | ||
"BBB","2014J","15021","TMA","54","10" | ||
"BBB","2014J","15022","TMA","110","20" | ||
"BBB","2014J","15023","TMA","152","35" | ||
"BBB","2014J","15024","TMA","201","35" | ||
"BBB","2014J","15025","Exam","","100" | ||
"CCC","2014B","24286","CMA","18","2" | ||
"CCC","2014B","24287","CMA","67","7" | ||
"CCC","2014B","24288","CMA","137","8" | ||
"CCC","2014B","24289","CMA","207","8" | ||
"CCC","2014B","24282","TMA","32","9" | ||
"CCC","2014B","24283","TMA","102","22" | ||
"CCC","2014B","24284","TMA","151","22" | ||
"CCC","2014B","24285","TMA","200","22" | ||
"CCC","2014B","24290","Exam","","100" | ||
"CCC","2014B","40087","Exam","","100" | ||
"CCC","2014J","24295","CMA","18","2" | ||
"CCC","2014J","24296","CMA","67","7" | ||
"CCC","2014J","24297","CMA","144","8" | ||
"CCC","2014J","24298","CMA","214","8" | ||
"CCC","2014J","24291","TMA","32","9" | ||
"CCC","2014J","24292","TMA","109","22" | ||
"CCC","2014J","24293","TMA","158","22" | ||
"CCC","2014J","24294","TMA","207","22" | ||
"CCC","2014J","24299","Exam","","100" | ||
"CCC","2014J","40088","Exam","","100" | ||
"DDD","2013B","25341","CMA","23","2" | ||
"DDD","2013B","25342","CMA","51","3" | ||
"DDD","2013B","25343","CMA","79","3" | ||
"DDD","2013B","25344","CMA","114","4" | ||
"DDD","2013B","25345","CMA","149","4" | ||
"DDD","2013B","25346","CMA","170","3" | ||
"DDD","2013B","25347","CMA","206","6" | ||
"DDD","2013B","25334","TMA","25","7.5" | ||
"DDD","2013B","25335","TMA","53","10" | ||
"DDD","2013B","25336","TMA","81","12.5" | ||
"DDD","2013B","25337","TMA","116","15" | ||
"DDD","2013B","25338","TMA","151","15" | ||
"DDD","2013B","25339","TMA","200","15" | ||
"DDD","2013B","25340","Exam","240","100" | ||
"DDD","2013J","25348","TMA","25","10" | ||
"DDD","2013J","25349","TMA","53","12.5" | ||
"DDD","2013J","25350","TMA","88","17.5" | ||
"DDD","2013J","25351","TMA","123","20" | ||
"DDD","2013J","25352","TMA","165","20" | ||
"DDD","2013J","25353","TMA","207","20" | ||
"DDD","2013J","25354","Exam","261","100" | ||
"DDD","2014B","25355","TMA","25","10" | ||
"DDD","2014B","25356","TMA","53","12.5" | ||
"DDD","2014B","25357","TMA","74","17.5" | ||
"DDD","2014B","25358","TMA","116","20" | ||
"DDD","2014B","25359","TMA","158","20" | ||
"DDD","2014B","25360","TMA","200","20" | ||
"DDD","2014B","25361","Exam","241","100" | ||
"DDD","2014J","25362","TMA","20","5" | ||
"DDD","2014J","25363","TMA","41","10" | ||
"DDD","2014J","25364","TMA","62","10" | ||
"DDD","2014J","25365","TMA","111","25" | ||
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"DDD","2014J","25367","TMA","195","25" | ||
"DDD","2014J","25368","Exam","","100" | ||
"EEE","2013J","30709","TMA","33","16" | ||
"EEE","2013J","30710","TMA","68","28" | ||
"EEE","2013J","30711","TMA","124","28" | ||
"EEE","2013J","30712","TMA","159","28" | ||
"EEE","2013J","30713","Exam","235","100" | ||
"EEE","2014B","30714","TMA","33","16" | ||
"EEE","2014B","30715","TMA","68","28" | ||
"EEE","2014B","30716","TMA","117","28" | ||
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"EEE","2014B","30718","Exam","228","100" | ||
"EEE","2014J","30719","TMA","33","16" | ||
"EEE","2014J","30720","TMA","68","28" | ||
"EEE","2014J","30721","TMA","131","28" | ||
"EEE","2014J","30722","TMA","166","28" | ||
"EEE","2014J","30723","Exam","235","100" | ||
"FFF","2013B","34865","CMA","222","0" | ||
"FFF","2013B","34866","CMA","222","0" | ||
"FFF","2013B","34867","CMA","222","0" | ||
"FFF","2013B","34868","CMA","222","0" | ||
"FFF","2013B","34869","CMA","222","0" | ||
"FFF","2013B","34871","CMA","222","0" | ||
"FFF","2013B","34870","CMA","222","0" | ||
"FFF","2013B","34860","TMA","19","12.5" | ||
"FFF","2013B","34861","TMA","47","12.5" | ||
"FFF","2013B","34862","TMA","89","25" | ||
"FFF","2013B","34863","TMA","131","25" | ||
"FFF","2013B","34864","TMA","166","25" | ||
"FFF","2013B","34872","Exam","222","100" | ||
"FFF","2013J","34878","CMA","236","0" | ||
"FFF","2013J","34879","CMA","236","0" | ||
"FFF","2013J","34880","CMA","236","0" | ||
"FFF","2013J","34881","CMA","236","0" | ||
"FFF","2013J","34882","CMA","236","0" | ||
"FFF","2013J","34884","CMA","236","0" | ||
"FFF","2013J","34883","CMA","236","0" | ||
"FFF","2013J","34873","TMA","19","12.5" | ||
"FFF","2013J","34874","TMA","47","12.5" | ||
"FFF","2013J","34875","TMA","96","25" | ||
"FFF","2013J","34876","TMA","131","25" | ||
"FFF","2013J","34877","TMA","173","25" | ||
"FFF","2013J","34885","Exam","236","100" | ||
"FFF","2014B","34891","CMA","227","0" | ||
"FFF","2014B","34892","CMA","227","0" | ||
"FFF","2014B","34893","CMA","227","0" | ||
"FFF","2014B","34894","CMA","227","0" | ||
"FFF","2014B","34895","CMA","227","0" | ||
"FFF","2014B","34897","CMA","227","0" | ||
"FFF","2014B","34896","CMA","227","0" | ||
"FFF","2014B","34886","TMA","24","12.5" | ||
"FFF","2014B","34887","TMA","52","12.5" | ||
"FFF","2014B","34888","TMA","87","25" | ||
"FFF","2014B","34889","TMA","129","25" | ||
"FFF","2014B","34890","TMA","171","25" | ||
"FFF","2014B","34898","Exam","227","100" | ||
"FFF","2014J","34904","CMA","241","0" | ||
"FFF","2014J","34905","CMA","241","0" | ||
"FFF","2014J","34906","CMA","241","0" | ||
"FFF","2014J","34907","CMA","241","0" | ||
"FFF","2014J","34908","CMA","241","0" | ||
"FFF","2014J","34910","CMA","241","0" | ||
"FFF","2014J","34909","CMA","241","0" | ||
"FFF","2014J","34899","TMA","24","12.5" | ||
"FFF","2014J","34900","TMA","52","12.5" | ||
"FFF","2014J","34901","TMA","94","25" | ||
"FFF","2014J","34902","TMA","136","25" | ||
"FFF","2014J","34903","TMA","199","25" | ||
"FFF","2014J","34911","Exam","241","100" | ||
"GGG","2013J","37418","CMA","229","0" | ||
"GGG","2013J","37419","CMA","229","0" | ||
"GGG","2013J","37420","CMA","229","0" | ||
"GGG","2013J","37421","CMA","229","0" | ||
"GGG","2013J","37422","CMA","229","0" | ||
"GGG","2013J","37423","CMA","229","0" | ||
"GGG","2013J","37415","TMA","61","0" | ||
"GGG","2013J","37416","TMA","124","0" | ||
"GGG","2013J","37417","TMA","173","0" | ||
"GGG","2013J","37424","Exam","229","100" | ||
"GGG","2014B","37428","CMA","222","0" | ||
"GGG","2014B","37429","CMA","222","0" | ||
"GGG","2014B","37430","CMA","222","0" | ||
"GGG","2014B","37431","CMA","222","0" | ||
"GGG","2014B","37432","CMA","222","0" | ||
"GGG","2014B","37433","CMA","222","0" | ||
"GGG","2014B","37425","TMA","61","0" | ||
"GGG","2014B","37426","TMA","117","0" | ||
"GGG","2014B","37427","TMA","166","0" | ||
"GGG","2014B","37434","Exam","222","100" | ||
"GGG","2014J","37438","CMA","229","0" | ||
"GGG","2014J","37439","CMA","229","0" | ||
"GGG","2014J","37440","CMA","229","0" | ||
"GGG","2014J","37441","CMA","229","0" | ||
"GGG","2014J","37442","CMA","229","0" | ||
"GGG","2014J","37443","CMA","229","0" | ||
"GGG","2014J","37435","TMA","61","0" | ||
"GGG","2014J","37436","TMA","124","0" | ||
"GGG","2014J","37437","TMA","173","0" | ||
"GGG","2014J","37444","Exam","229","100" |
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db2_for_machine_learning_samples/Db2 Hackathon - Learnware/data/courses.csv
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"code_module","code_presentation","module_presentation_length" | ||
"AAA","2013J","268" | ||
"AAA","2014J","269" | ||
"BBB","2013J","268" | ||
"BBB","2014J","262" | ||
"BBB","2013B","240" | ||
"BBB","2014B","234" | ||
"CCC","2014J","269" | ||
"CCC","2014B","241" | ||
"DDD","2013J","261" | ||
"DDD","2014J","262" | ||
"DDD","2013B","240" | ||
"DDD","2014B","241" | ||
"EEE","2013J","268" | ||
"EEE","2014J","269" | ||
"EEE","2014B","241" | ||
"FFF","2013J","268" | ||
"FFF","2014J","269" | ||
"FFF","2013B","240" | ||
"FFF","2014B","241" | ||
"GGG","2013J","261" | ||
"GGG","2014J","269" | ||
"GGG","2014B","241" |
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This is internal-only and won't be broadly useful to external consumers of this sample. Should we change or remove this?
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Yes, I think you are right. I took it out of the README.md now. It should be good to go