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
Explore the science and therapeutic potential of psychedelics in this course led by experts from the Johns Hopkins Center for Psychedelic and Consciousness Research. You\'ll learn about the history... more
The energy revolution in underway. Renewable energy is growing at an astounding pace - notably in electricity. Wind turbines and solar photovoltaic (PV) systems account for most new power plants... more
In this Network Security Fundamentals course you will gain an understanding of the fundamental tenants of network security and review the general concepts involved in maintaining a secure network... more
This Specialization is intended for researchers and business experts seeking state-of-the-art knowledge in advanced science and technology. The 4 courses cover details on Big Data (Hadoop, Spark,... more
Thousands of new epidemiological studies are conducted every year and their results can have a profound impact on how we live our lives. Decisions regarding the food you eat, how much you exercise,... more
Powered by
