Dmitriy Bolotov

Hello!

This site shares data science projects and open-source tools I've worked on, in the hope that they're useful.

I now run a consulting practice where I offer hands-on AI workshops and advising for business teams. Say hi on LinkedIn.

Time Series Smoothing Visualizer - Interactive app that helps users understand six common smoothing techniques for time series data. | GitHub

Visual Time Series Generator - Interactive app for generating time series data. Includes options for missing values and anomalies. | GitHub

DS QuickRef - A concise, opinionated reference for practical data science and machine learning workflows in Python.

Python and R packages for exploratory analysis, model development, and deployment:

minieda – Minimalist Python package for summarizing DataFrames.
pmml – Export predictive models and preprocessing steps from R to PMML, an open standard for deployment.
neighbr – K-nearest neighbors for classification, regression, and clustering in R.
amelie – Anomaly detection using maximum likelihood estimation in R. | Intro

Predicting Gym Member Churn for Targeted Retention – Includes cohort breakdowns, predictive model, risk segmentation, and targeted retention strategies. | Medium article | Jupyter notebook

Synthetic Data Generation – Generating synthetic data for a bank marketing campaign using SDV. | Jupyter notebook | GitHub