Several data science applications using scikit-learn and streamlit. These applications cover simple usage of streamlit, data exploration, classification, and regression on standard machine learning datasets. In addition, several datasets were also extracted for exploration, such as the SP500 and cryptocurrency markets.
| Type | Program | Command |
|---|---|---|
| Simple Examples | Stock Price | streamlit run "01 - Simple Examples\Stock Price.py" |
| Simple Examples | DNA Count | streamlit run "01 - Simple Examples\DNA Count.py" |
| Exploratory Data Analysis | EDA Basketball | streamlit run "02 - Exploratory Data Analysis\EDA Basketball.py" |
| Exploratory Data Analysis | EDA Football | streamlit run "02 - Exploratory Data Analysis\EDA Football.py" |
| Exploratory Data Analysis | EDA SP500 | streamlit run "02 - Exploratory Data Analysis\EDA SP500.py" |
| Exploratory Data Analysis | EDA Crypto | streamlit run "02 - Exploratory Data Analysis\EDA Crypto.py" |
| Classification | Iris | streamlit run "03 - Classification\Iris.py" |
| Classification | Penguins | streamlit run "03 - Classification\Penguins.py" |
| Regression | Boston Housing | streamlit run "04 - Regression\Boston Housing.py" |
| Regression | Visual Regression | streamlit run "04 - Regression\Visual Regression.py" |
