- Machine Learning
- Health Policy
- Data Preprocessing
- Model Evaluation
- Artificial Neural Networks
- Healthcare Ethics
- Reinforcement Learning
- Applied Machine Learning
- Convolutional Neural Networks
- Data Ethics
- Responsible AI
- Machine Learning Algorithms
Fundamentals of Machine Learning for Healthcare
Completed by Bernard alexis Trillat
January 14, 2021
14 hours (approximately)
Bernard alexis Trillat'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
