ML6

Heart Failure Diagnostics is a project aimed at using Artificial Intelligence and Data Consulting to develop innovative solutions for early detection and monitoring of heart failure in patients. With a focus on leveraging advanced technologies, the project aims to improve the accuracy and efficiency of diagnostic processes for heart failure.

The Sports Intelligence Engine is a cutting-edge project that leverages data consulting to provide actionable insights and analysis for sports organizations. By utilizing advanced data analytics and machine learning techniques, the project aims to revolutionize the way sports teams make decisions and optimize their performance.

Battery Life Optimization is a project aimed at improving the efficiency and longevity of battery life in electronic devices. Through data consulting services, we analyze and identify key factors that affect battery performance.

Anomaly Detection Hypotheek is a project that focuses on utilizing advanced data analytics techniques to detect unusual patterns or outliers in mortgage data. By identifying anomalies in the data, this project aims to help mortgage lenders and financial institutions identify potential fraud, errors, or inconsistencies in their loan portfolios.

Video indexing and ML for metadata tagging is a project aimed at automating the process of tagging videos with relevant metadata using machine learning techniques. This project focuses on improving video search, recommendation, and organization by extracting meaningful information from the content.

The project "Improving quality process by visual inspection" aims to enhance the quality control procedures in a manufacturing setting by incorporating visual inspection techniques. By utilizing advanced imaging technology and machine learning algorithms, the project seeks to automate the inspection process and minimize human error.

SEM Image Classification is a project aimed at developing a machine learning model to classify scanning electron microscope (SEM) images into various categories. The project involves analyzing and processing large datasets of SEM images to train the model.

Machine learning in Production is a project aimed at implementing and deploying machine learning models in real-world applications. This project focuses on the transition from experimental models to robust production systems that can handle large-scale data and deliver reliable results.

The Dashboard project is a cutting-edge system designed to detect instances of wine loss within a wine storage facility. By utilizing artificial intelligence technology and data consulting services, this system is able to accurately monitor and track inventory levels in real-time.