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Examples – Machine Gnostics

Explore practical examples and Jupyter notebooks demonstrating the use of Machine Gnostics for various machine learning tasks. Each example includes code, explanations, and links to downloadable notebooks.

Example Notebooks

  1. Small Data Regression – Linear Regression A simple linear regression example using a small dataset to illustrate the basics of model fitting and evaluation.

  2. Wine Quality: Multidimensional Linear Regression
    Regression on the wine quality dataset with multiple input features (X), showcasing how to handle multivariate data using linear regression.

  3. Small Data Polynomial Regression
    Polynomial regression on a small dataset, demonstrating how to fit and evaluate nonlinear relationships.

  4. Wine Quality: Multidimensional Polynomial Regression Polynomial regression applied to the wine quality dataset with multiple features, highlighting advanced regression techniques.

  5. Basic Binary Logistic Regression
    A straightforward binary classification example using logistic regression, including model training and evaluation.

  6. Logistic Regression with MLflow Integration
    An end-to-end example of logistic regression with experiment tracking and reproducibility using MLflow.

Access the Notebooks

You can download or view the Jupyter notebooks for each example from the examples directory in the repository.

Examples

More details on the Machine Gnostics Foundation fine here