Diabetes Disease Detection with XG-Boost and Neural Networks
About this Course
In this project-based course, we will build, train and test a machine learning model to detect diabetes with XG-boost and Artificial Neural Networks. The objective of this project is to predict whether a patient has diabetes or not based on their given features and diagnostic measurements such as number of pregnancies, insulin levels, Body mass index, age and blood pressure.Created by: Coursera Project Network
Related Online Courses
At the end of this project, you will have all the basic skills to use Piktochart, a software and online tool for creating and editing infographics and Marketing designs of all kinds. You will be... more
In this course, learners will become familiar with principles and theories of global health problems, and major challenges and controversies in improving global population health as well as... more
In this course, you will learn fundamental cloud computing concepts. This course covers key benefits of cloud computing, cloud service models such as SaaS and IaaS; public, private and hybrid cloud... more
This Specialization is intended for machine learning researchers and practitioners who are seeking to develop practical skills in the popular deep learning framework TensorFlow.\\n\\nThe first... more
This course is designed for high school students preparing to take the AP* Physics 1 Exam. * AP Physics 1 is a registered trademark of the College Board, which was not involved in the production... more
Powered by
