Software Development Kit (SDK) for the Intel® Geti™ platform for Computer Vision AI model training.

Develop a deep learning model capable of predicting traffic flow in urban environments. The model will utilize historical traffic data, weather conditions, and road configurations to forecast traffic patterns. This information can be invaluable for traffic management systems, helping to optimize traffic signals and reduce congestion, ultimately.

🔬 Flask API for the Neuro Gambling Scanner project – Predicts gambling addiction risk using machine learning and returns personalized interventions.

Flask for training/testing Watson, FastText, Gensen Embeddings and hDBScan. Plus it supports MLFlow for model info logging.

Manage model artifacts throughout the model development process.

This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more!

A streamlined app for traditional ML model training and deployment. Features include interactive data visualization, model optimization tools, and automated deployment capabilities. Ideal for data scientists and ML engineers looking to simplify their workflow.