Deep Learning with PyTorch for Medical Image Analysis

What you'll learn
Learn how to use NumPy
Learn classic machine learning theory principals
Foundations of Medical Imaging
Data Formats in Medical Imaging
Creating Artificial Neural Networks with PyTorch
Use PyTorch-Lightning for state of the art training
Visualize the decision of a CNN
2D & 3D data handling
Automatic Cancer Segmentation

Description
Did you ever want to apply Deep Neural Networks to more than MNIST, CIFAR10 or cats vs dogs?

Do you want to learn about state of the art Machine Learning frameworks while segmenting cancer in CT-images?

Then this is the right course for you!

Welcome to one of the most comprehensive courses on Deep Learning in medical imaging!

This course focuses on the application of state of the art Deep Learning architectures to various medical imaging challenges.

You will tackle several different tasks, including cancer segmentation, pneumonia classification, cardiac detection and many more.

The following topics are covered:

NumPy

Machine Learning Theory

Test/Train/Validation Data Splits

Model Evaluation - Regression and Classification Tasks

Tensors with PyTorch

Convolutional Neural Networks

Medical Imaging

Interpretability of a network's decision - Why does the network do what it does?

A state of the art high level pytorch library: pytorch-lightning

Tumor Segmentation

Three-dimensional data

and many more

Why choose this specific course ?

This course provides unique knowledge on the application of deep learning to highly complex and non-standard (medical) problems (in 2D and 3D)

All lessons include clearly summarized theory and code-along examples, so that you can understand and follow every step.

Powerful online community with our QA Forums with thousands of students and dedicated Teaching Assistants, as well as student interaction on our Discord Server.

They will learn skills and techniques that the vast majority of AI engineers do not have!

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Jose, Marcel, Sergios & Tobias

Who this course is for:
Python developers and Machine Learning engineers who want to learn how to tackle real world problems occurring on a daily basis in the field of medical imaging with the help of Deep Convolutional Neural Networks.
Everybody who wants to learn more about the joint field of AI and Medical Imaging & how it works
Developers familiar with basic Deep Learning knowledge who want to apply their skills to more than toy problems
Medical professionals interested in how AI actually works in medicine

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