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MarijuanaAnalyzer: an Intelligent Visualization and Analysis Web App TEAM 47 11/20/2020 1. DESCRIPTION: ---------------------------------------------------------------------------------- MarijuanaAnalyzer is a intelligent web app integrated with interactive data visualization as well as a predictor backed by multiple machine learning models. We provide a comprehensive overview of marijuana through dynamic data visualization. Also, the user can predict the impact of marijuana on mental health and abuses of other drugs based on customized demographic information. The ultimate goal is to provide insights into policy makers’ decision making. Also, we hope to offer a more informative education for our web app users. PACKAGES/FILES: Web app repository (https://github.gatech.edu/ylu635/marijuana): css: css files associated with index.html and ml.html. data: data used in data visualization. js: Javascript code for data visualization as well as machine learning predictors lib: D3 library index.html: html file for main page. ml.html: html file for machine learning predictor page. predictors: python code for training and generating machine learning models AWS lambda repository (https://github.gatech.edu/ftian39/marijuana_effects_team_47_lambda): code: code for AWS lambda used in predictors devEnv.json: a file for local test template.yaml: AWS cloudforamtion ---------------------------------------------------------------------------------- 2. INSTALLATION: ---------------------------------------------------------------------------------- unzip submitted team047final.zip (or "git clone https://github.gatech.edu/ylu635/marijuana.git" for web app only) ---------------------------------------------------------------------------------- 3. EXECUTION: ---------------------------------------------------------------------------------- LOCAL EXECUTION: 1) change directory: "cd <path to the <marijuana> project folder under team47final/CODE folder>" 2) local execution: "python -m http.server 8000" HOSTED STATIC WEB PAGE: go to url "https://lukeyanggb.github.io/" ---------------------------------------------------------------------------------- 4. APPENDIX ---------------------------------------------------------------------------------- TEAM MEMBERS: Muzi Bi, Yang Lu, Fangxia Tian, Jing Ren, Jian Wang, Yutong Wu LANGUAGES: Python, Javascript, HTML, CSS LIBRARIES D3.js, scikit-learn, Pandas, Seaborn, Numpy, Scipy, Matplotlib, Joblib FRAMEWORK: Bootstrap CLOUD RESOURCES: AWS API Gateway, AWS Lambda, AWS S3 MAIN DATASET: https://www.datafiles.samhsa.gov/study-series/national-survey-drug-use-and-health-nsduh-nid13517 ----------------------------------------------------------------------------------
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