Medical Diagnosis using Support Vector Machines

About this guided project

In this one hour long project-based course, you will learn the basics of support vector machines using Python and scikit-learn. The dataset we are going to use comes from the National Institute of Diabetes and Digestive and Kidney Diseases, and contains anonymized diagnostic measurements for a set of female patients. We will train a support vector machine to predict whether a new patient has diabetes based on such measurements. By the end of this course, you will be able to model an existing dataset with the goal of making predictions about new data. This is a first step on the path to mastering machine learning. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

What skills will you gain?

Predictive Modeling

Statistical Modeling

Predictive Analytics

Data Science

Supervised Learning

Machine Learning Methods

Statistical Machine Learning

Machine Learning Algorithms

Applied Machine Learning

Machine Learning

Artificial Intelligence and Machine Learning (AI/ML)