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  • Nairobi, Kenya
  • 03:04 (UTC +03:00)

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okech-glitch/README.md

LinkedIn Email


Current Focus

  • Advanced Analytics: Exploring time series forecasting and deep learning applications
  • Full-Stack Innovation: Building scalable web applications with modern frameworks
  • Data Visualization: Creating interactive dashboards that tell compelling data stories
  • AI Integration: Incorporating machine learning into practical business solutions

Technical Skills

Data Analytics & Science

Python R SQL Pandas Polars NumPy Matplotlib Seaborn Scikit-learn Tableau Power BI

Frontend Development

HTML5 CSS3 JavaScript React Vue.js TypeScript

Backend Development

Node.js Express.js Django Flask FastAPI

Databases & Tools

MySQL PostgreSQL MongoDB Git Docker AWS


Featured Projects

Agri-Adapt AI - AI-Powered Agricultural Resilience Platform

3rd Place Winner - Inflection AI Hackathon | Africa Impact Network

Python FastAPI Next.js React TypeScript Polars

Empowering Kenyan farmers with AI-driven drought resilience insights to make informed crop decisions and reduce agricultural losses by up to 30%. Features Random Forest ML model with 70% accuracy, real-time predictions, and mobile-first design.

View Project Live Demo


Customer Churn Prediction - Fullstack ML Project

End-to-end ML system predicting bank customer churn with a modern web interface

FastAPI React TypeScript Scikit-learn XGBoost LightGBM CatBoost Docker

Comprehensive churn prediction system featuring EDA, feature engineering, multiple ML algorithms (XGBoost, LightGBM, CatBoost), REST API for model serving, and a React dashboard for real-time predictions and model analysis. Target ROC-AUC > 0.85.

View Project

  • Quick start: pip install -r requirements.txt · npm install · run FastAPI + React
  • Features: Model comparison, feature importance, batch/single predictions, exportable results

Grocery Basket Insights - Market Basket Analysis Platform

AI-powered demo app for analyzing customer transactions and predicting product bundles

Flask React Scikit-learn Pandas TailwindCSS

This platform leverages association rule mining to extract actionable product associations from retail data. Features include interactive charts, downloadable CSVs, top-10 bundle recommendations, and custom filters (customer ID, confidence). Fullstack implementation with Flask backend and React frontend.

View Project

  • Association Rule Mining for frequent itemsets
  • Downloadable results & interactive chart visualizations
  • Built-in dark/light mode, filtering, and performance metrics

Pinned Loading

  1. customer-churn-prediction customer-churn-prediction Public

    JavaScript

  2. grocery-basket-insights grocery-basket-insights Public

    Market basket analysis to predict cross-selling opportunities

    Python

  3. Python-Data-Visualization Python-Data-Visualization Public

    Data analytics reports and visualizations

    Jupyter Notebook

  4. health-prognosis-demo health-prognosis-demo Public

    Participants mine electronic health records (EHR) and medical data to predict disease outcomes (e.g., risk of readmission or mortality). Models could use classification techniques to identify risk …

    JavaScript