Diabetes Disease Detection with XG-Boost and Neural Networks

In this project-based course, you will delve into the world of machine learning to build, train, and test a model for diabetes detection. Through a hands-on approach, you'll gain a comprehensive understanding of utilizing XG-Boost and Artificial Neural Networks to predict whether a patient has diabetes.

Throughout the course, you will explore the process of training an ANN and XG-Boost algorithms to solve classification type problems, enabling you to apply these techniques to real-world scenarios. Additionally, you will master the art of performing Data Visualization and Exploratory Data Analysis, essential skills for any aspiring data scientist or machine learning practitioner.

• Build, Train and Test XG-Boost and Artificial Neural Networks Model
• Train an ANN and XG-Boost algorithms to solve classification type problems
• Perform Data Visualization and Exploratory Data Analysis