Home AI Courses Fundamentals of ML in Healthcare

Fundamentals of ML in Healthcare

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Gain an understanding of the fundamental methods for training machine learning models with data, investigate advanced neural network architectures, and comprehend the challenges posed by dynamic medical practice on clinical machine learning applications by learning to bridge biostatistics, machine learning, and computer programming.

Key AI Functions:AI Healthcare,Machine Learning,Biostatistics,Neural Network

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Description for Fundamentals of ML in Healthcare

Establish critical connections between the disciplines of biostatistics, machine learning, and conventional computer programming.

Discover the latest in neural network architectures for a variety of applications, including object detection and segmentation, as well as text classification.

Discover critical methods for utilizing data to train, validate, and test machine learning models.

Develop an understanding of the impact of discontinuous timelines and dynamic medical practice on the development and deployment of clinical machine learning applications.

Level: Beginner

Certification Degree:Yes

Languages the Course is Available: 22

Offered by: On Coursera provided by Stanford University

Duration: 14 hours (approximately)

Schedule: Flexible

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