代写DTS101TC Introduction to Neural Networks代写Python编程

DTS101TC Introduction to Neural Networks

Coursework

Due: Sunday Apr.6^th, 2025 @ 24:00

Weight: 100%

Overview

This coursework is the sole assessment for DTS101TC and aims to evaluate your comprehension of the module. It consists of two parts: five individual assignments/questions and an image object detection project. Each assignment/question must be completed according to the instructions provided in the Python Jupyter Notebook, with all output cells saved alongside the code. A report for the image object detection project must be submitted with the code and data. AIGC tools are not allowed in this coursework.

Learning Outcomes

A. Develop an understanding of neural networks – their architectures, applications and limitations.

B. Demonstrate the ability to implement neural networks with a programming language

C. Demonstrate the ability to provide critical analysis on real-world problems and design suitable solutions based on neural networks.

Policy

Please submit your assignments (notebooks) via Gradescope. For the project, please prepare your report in PDF format and package your code and data as a ZIP file. If there are any errors in the program, include debugging information and show your analysis. Submit both the report and the ZIP code file via Learning Mall Core. Electronic submission is the only accepted method; hard copies will not be accepted.

After submission, you must download your file and check that it is viewable. Documents may become corrupted during the uploading process (e.g. due to slow internet connections). Students are responsible for submitting functional and correct files for assessment.