"Foot on Track" is an application designed to monitor running activities in real-time, authenticate users securely, and provide insightful performance analytics using machine learning.

An android application that allow the user to log in (and access to all his data), and connect to external distributors, in order to get the coffee generated by a Machine Learning algorithm

An end-to-end machine learning and data mining framework on Hadoop

A parser for scikit-learn exported text models to execute in the Java runtime.

This contains the most commonly used machine learning and deep learning models written from scratch without the use if any libraries except Numpy which is used for calculations

SUTD 50.003 ESC Indoor Tracking Project with UnaBiz

It's my 3rd Semester OOP lab Project

Fast Random Forests implementation for Weka. Streamlined version of Fan Supek's FastRandomForest.

We present a framework called TLF that builds a classifier for the target domain having only few labeled training records by transferring knowledge from the source domain having many labeled records. While existing methods often focus on one issue and leave the other one for the further work, TLF is capable of handling both issues simultaneously…

Utilizando o Spark para o desenvolvimento de algoritmos de Machine Learning (Regressão Linear e Regressão Logistica) com Java através do HDFS, para o trabalho final do 1º semestre de Infraestrutura de Big Data.

Algumas estruturas de repetição em Java

An example of how to provide a CD pipeline enabled h2o Machine Learning project Edit

Low Birth Weight prediction ML model is deployed in an Android Application

A fast and easy to use decision tree learner in java

Lab solutions for Artificial Intelligence ("Umjetna inteligencija") course at FER 2019/20 led by izv. prof. dr. sc. Jan Šnajder and doc. dr. sc. Marko Čupić

Java implementation of a Robust Random Cut Forest for streaming, unsupervised, adaptive anomaly detection

Distributed Random Forest in Apache Flink

Implementation of several classification algorithms in Java. In addition to algorithms, it was necessary to implement tools for reading data, validation and evaluation metrices.

ID3 + Random forest implementation in Java

This addresses the recognition of natural human actions in a video or in real time.