A case study in betting on the S&P 500 using the Kelly criterion
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Updated
Jun 16, 2024 - Jupyter Notebook
A case study in betting on the S&P 500 using the Kelly criterion
R Package for the Interactive Shiny Application for exploratory data analysis thru visualization
Build visual machine learning models with multidimensional general line coordinate visualizations by interactive classification and synthetic data generation tools.
A Simpel Mnist Flower's Interactive Data Visualization using Streamlit and GGPlot.
Objective, create an intuitive and user-friendly web-based application for visualizing and exploring NHANES data. This dashboard will enable users, including those with limited or no Python programming experience, to interact with NHANES data and generate informative visualizations to gain insights into various health-related aspects.
A collection of Jupyter notebooks for basic analysis of the data from the "BeatAML" study by Tyner et al. (2018)
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