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Explainable Generic ML Pipeline with MLflow

An article detailing how to build a flexible, explainable, and algorithm-agnostic ML pipeline with MLflow, focusing on preprocessing, model training, and SHAP-based explanations.

2024-11-27 Tags: mlops, pipeline, mlflow, shap, xai, data engineering, feature engineering, machine learning, eda by klotz

ASCVIT V1: Automatic Statistical Calculation, Visualization, and Interpretation Tool

ASCVIT V1 aims to make data analysis easier by automating statistical calculations, visualizations, and interpretations.

Includes descriptive statistics, hypothesis tests, regression, time series analysis, clustering, and LLM-powered data interpretation.

Accepts CSV or Excel files. Provides a data overview including summary statistics, variable types, and data points.
Histograms, boxplots, pairplots, correlation matrices.
t-tests, ANOVA, chi-square test.
Linear, logistic, and multivariate regression.
Time series analysis.
k-means, hierarchical clustering, DBSCAN.

Integrates with an LLM (large language model) via Ollama for automated interpretation of statistical results.