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- Level Intermediate
- Duration 2 hours
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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.Auto Summary
Explore the essentials of support vector machines in this one-hour project-based course focused on medical diagnosis using Python and scikit-learn. Analyze real-world diagnostic data to predict diabetes in patients. Ideal for professional-level learners in North America, this Coursera course offers a foundational step towards mastering machine learning. Available with a Starter subscription.