Learning Outcomes to be assessed:
Demonstrate a critical understanding of the theoretical principles and objectives of Deep Learning (DL)
Critically assess and select a range of DL concepts and techniques.
Programmes: MSc Artificial Intelligence (Machine Learning)
7144COMP Report on Theoretical Principles of Deep Learning Assignment-Liverpool University UK
This coursework focuses on the theoretical aspects of deep learning and its practical implications.Associated tools and techniques for undertaking the training and inferencing of a deep learning model for a particular scenario is also covered. For the first part of the coursework, you are required to write a six-page paper (double column IEEE format) on the topic of deep learning and related concepts using the materials taught in the lectures while undertaking independent research to reinforce the conclusions and opinions expressed in your paper. The second part of the coursework focuses on the practical implications and considerations of training a deep learning model while undertaking inferencing. Here you are required to construct a methodology for a given scenario taking into consideration the hardware, data and functional requirements.
Detail of the tasks
1) Deep learning concepts and discussion
BBC Autumn watch has launched a computer vision challenge to develop a deep learning object detection model to track the species of birds visiting gardens throughout autumn. They wish to use standard camera trap equipment which provides still image data with a resolution of 1024 x 768
pixels. You are required to write a research paper using the templated provided on Canvas called(Course work 1 template .docx) and the associated image data (Birds.zip). Please note that the format settings of this template are not to be changed. Your paper must include the following
sections and discussion: