Medical Diagnosis using Support Vector Machines

4.5

61 个评分

提供方

2,095 人已注册

在此指导项目中,您将:
1 hour
中级
无需下载
分屏视频
英语(English)
仅限桌面

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.

您要培养的技能

  • Python Programming

  • Machine Learning

  • Scikit-Learn

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

审阅

来自MEDICAL DIAGNOSIS USING SUPPORT VECTOR MACHINES的热门评论

查看所有评论

常见问题