This course is intended for persons involved in machine learning who are interested in medical applications, or vice versa, medical professionals who are interested in the methods modern computer science has to offer to their field. We will cover health data analysis, different types of neural networks, as well as training and application of neural networks applied on real-world medical scenarios.
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이 강좌에 대하여
We recommend a solid foundation in one of the fields adjacent to the topic of the course, such as Computer Science, Machine Learning, Medicine.
배울 내용
Machine Learning, Health Data Processing
귀하가 습득할 기술
- Graphs
- Unsupervised Learning
- Autoencoder
- Deep Learning
We recommend a solid foundation in one of the fields adjacent to the topic of the course, such as Computer Science, Machine Learning, Medicine.
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일리노이대학교 어버너-섐페인캠퍼스
The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.
석사 학위 취득 시작
강의 계획표 - 이 강좌에서 배울 내용
Week 1 - Introduction
In the introduction we will introduce the topic of the course and present the background information.
Week 2 - Health Data
Health Data are generated in many different categories of medical services. We'll take a closer look at these, and what this means for Health Data standards.
Week 3 - Machine Learning Basics
The topic of this week is Machine Learning. We'll look at
Week 4 - Deep Neural Networks (DNN)
Deep Learning for Healthcare 특화 과정 정보
This specialization is intended for persons involved in machine learning who are interested in medical applications, or vice versa, medical professionals who are interested in the methods modern computer science has to offer to their field. We will cover health data analysis, different types of neural networks, as well as training and application of neural networks applied on real-world medical scenarios.

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