- Machine Learning Algorithms
- Artificial Neural Networks
- Healthcare Ethics
- Convolutional Neural Networks
- Artificial Intelligence and Machine Learning (AI/ML)
- Model Evaluation
- Deep Learning
- Reinforcement Learning
- Applied Machine Learning
- Machine Learning
- Data Ethics
- Health Policy
Fundamentals of Machine Learning for Healthcare
Completed by James Timothy Humphreys
October 6, 2021
14 hours (approximately)
James Timothy Humphreys's account is verified. Coursera certifies their successful completion of Fundamentals of Machine Learning for Healthcare
What you will learn
Define important relationships between the fields of machine learning, biostatistics, and traditional computer programming.
Learn about advanced neural network architectures for tasks ranging from text classification to object detection and segmentation.
Learn important approaches for leveraging data to train, validate, and test machine learning models.
Understand how dynamic medical practice and discontinuous timelines impact clinical machine learning application development and deployment.
Skills you will gain
