PyTorch and Monai for AI Healthcare Imaging - Python Machine Learning Course

Dive into a comprehensive Python machine learning course focused on AI healthcare imaging using PyTorch and Monai. Master the creation of an automatic liver segmentation algorithm while improving your computer vision skills. Explore the U-Net architecture, learn to install necessary software and packages, and discover how to find and prepare datasets. Gain hands-on experience with preprocessing techniques, understand common errors and their solutions, and delve into advanced concepts like Dice Loss and Weighted Cross Entropy. Progress through the training and testing phases, and learn how to utilize the provided GitHub repository for practical implementation. Enhance your machine learning expertise with this in-depth, healthcare-oriented course led by Mohammed El Amine MOKHTARI.

) Introduction.
) What is U-Net.
) Software Installation.
) Finding the Datasets.
) Preparing the Data.
) Installing the Packages.
) Preprocessing.
) Errors you May Face.
) Dice Loss.
) Weighted Cross Entropy.
) The Training Part.
) The Testing Part.
) Using the GitHub Repository.