Fundamentals of Machine Learning for Healthcare

What you will learn from the Fundamentals of Machine Learning for Healthcare

  • 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
  • Supervised Machine Learning Approaches
  • Traditional Supervised Machine Learning Approaches
  • Deep Learning and Neural Networks
  • Representing Unstructured Image and Text Data
  • Natural Language Processing and Recurrent Neural Networks
  • Convolutional Neural Networks
  • Advanced Neural Network Architectures
  • Statistical Approaches to Model Evaluation
  • Common Clinical Machine Learning Challenges
  • Medical Data Challenges in Machine Learning
  • Building Multidiciplinary Teams for Clinical Machine Learning

Course Instructors Matthew Lungren, Serena Yeung & Offered by Stanford University from Coursera

Course Duration: 12 hours to complete

Course is for Beginner Level

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