Python AutoML for Trading Systems and Sports Betting

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

Retentioneering: product analytics, data-driven CJM optimization, marketing analytics, web analytics, transaction analytics, graph visualization, process mining, and behavioral segmentation in Python. Predictive analytics over clickstream, AB tests, machine learning, and Markov Chain simulations.

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

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.

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.

Framework for developing low-code/no-code payroll solutions focused on automation, scalability and testability.

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.

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

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

A Data science and Analytics project with the main aim of doing some Descriptive and Exploratory Data Analysis and then applying predictive modelling for predicting why and which are the best and most experienced employees leaving prematurely?

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)

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.

Machine Learning - Linear Regression_Ecommerce_Prediction