Introduction to Artificial Neural Networks in Python

Description

To ensure eligibility for a place, please register with your University email address.

Apply for a place at our upcoming workshop! Tom Joseph Pollard from the MIT Institute for Medical Engineering and Science will be hosting an online workshop on Machine Learning with Python. This will include examples from medicine, such as artificial neural networks for disease classification in chest X-rays but is applicable to any of our research themes. During the lesson attendees will prepare and visualise data for algorithm development, build and train a neural network for disease classification, and evaluate performance.

Learners gain:

• an understanding of key concepts in machine learning and an awareness of ethical issues,
• skills to apply machine learning to real-life tasks, and
• motivation and empowerment for continued learning.

The lesson follows a health narrative using anonymised, real-world patient data (x-ray images; electronic health records). Knowledge gained will be domain agnostic.

Requirements

Familiarity with Python is helpful, but not required. This is an introductory-level course.

Tech

Python notebooks in hosted environment; TensorFlow; Git/GitHub; Etherpad, Zoom.