Python AutoML for Trading Systems and Sports Betting

A microservices-based Streaming and Batch data processing in Cloud Foundry and Kubernetes

Python toolkit, MCP server, and agent skills for reproducible, auditable clickstream and event log analytics. Helps AI agents, data scientists and analysts build, validate, and cross-check product analytics, quantitative UX, customer journeys, graph-based user flows, behavioral segmentation, A/B tests, process mining models, Markov chain simulation

Code for Agile Data Science 2.0, O'Reilly 2017, Second Edition

Horizontal Pod Autoscaler built with predictive abilities using statistical models

🌝 Lottery prediction besides of following "law of proability","Probability: Independent Events", there are still "Saying "a Tail is due", or "just one more go, my luck is due to change" is called The Gambler's Fallacy" existed.

Data Science algorithms for Qlik implemented as a Python Server Side Extension (SSE).

R package for Customer Behavior Analysis

Data-Analyst-Roadmap for Professionals. This roadmap contains 8 Chapters that can be completed in 8 weeks, whether you are a fresher in the field or an experienced professional who wants to transition into Data Analysis.

PANDORA 💻

Analysing the content of an E-commerce database that contains list of purchases. Based on the analysis, I develop a model that allows to anticipate the purchases that will be made by a new customer, during the following year from its first purchase.

Introducing a Dash web app that guides the analysis of time series datasets, using sARIMA models

Machine Learning - Linear Regression_Ecommerce_Prediction

A High-Performance Data Science Toolkit for the Earth Sciences

A machine learning plugin for Elasticsearch providing aggregations to compute multiple linear regression on search results in real-time for predictive analytics.

This program predicts the price of GOOG stock for a specific day using the Machine Learning algorithm called Support Vector Regression (SVR) Linear Regression. Importing flask module in the project is mandatory An object of Flask class is our WSGI application.

Business Case Study to predict customer churn rate based on Artificial Neural Network (ANN), with TensorFlow and Keras in Python. This is a customer churn analysis that contains training, testing, and evaluation of an ANN model. (Includes: Case Study Paper, Code)

AI-Powered Predictive Maintenance & Fault Diagnosis through Model Context Protocol. An open-source framework for integrating Large Language Models with predictive maintenance and fault diagnosis workflows.

This repository provides the code examples for the corresponding blog posts. In case you have questions, feel free to contact me directly.