Important notes:
- This course is not a regular course with classes for students.
- This repository has been created to accomplish an online workshop (a training organized for newly recruited teachers).
Briefly, a Neural Network (NN) is defined as an algorithm (tries to mimic biological phenomenon) as a computing system to process information. NN consists of a number of highly interconnected neurons organized in layers. NN objective is to perform complex calculations to find patterns that help to solve a problem.
Deep learning is an exciting, young field that specializes in discovering and extracting intricate structures in large, unstructured datasets for parameterizing artificial neural networks with many layers. Since deep learning has pushed the state-of-the-art in many applications, it’s become indispensable for modern technology. This is owed to the vast utility of deep learning for tackling complex tasks in the fields of computer vision and natural language processing, tasks that humans are good at but are traditionally challenging for computers. This includes tasks such as image classification, object detection, and speech recognition.
The focus of this course will be on understanding artificial neural networks and deep learning algorithmically (discussing the math behind these methods on a basic level) and implementing network models in code as well as applying these to real-world datasets.
- Instructor: Abdelghani Dahou