EE5438Applied Deep Learning

这门课学什么

课程概述与目标

The purpose of this course is to familiarize students with state-of-the-art deep learning techniques adopted by the industry, such as MPL, CNN, LSTM, Transformer, BERT, GPT-3, ChatGPT, LLaMA LLaVA and more. Students will learn theoretical and practical concepts of deep neural networks, including optimization, inference, architecture, and applications. After completing this course, students should be able to develop and train deep neural networks, reproduce research results, and conduct original research. Additionally, students will use the Python programming language to implement deep learning applications through the PyTorch package.

课程内容

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我能不能修这门课

先修、建议先备和并修要求分别查看；等同及互斥条件也会影响选课。and 表示同时满足，or 表示备选；组合条件按下方原文分组阅读。

先修条件

无（校方注明 Nil）

建议先备知识

[MA2011 Multi-variable Calculus and Linear Algebra]; and [MA3160 Probability and Stochastic Processes]; and [EE3206 Java Programming and Applications]

并修要求

该版官方课纲未列明该项。

其他修读要求

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等同课程及条件

无（校方注明 Nil）

互斥课程及条件

EE4016 Applications of AI with Deep Learning

怎么考，怎样才算通过

考核方式

Continuous assessment: 50%; Examination: 50%; Examination duration: 2 hours

通过条件

Remark: To pass the course, students are required to achieve at least 30% in course work and 30% in the examination. # may include homework, tutorial exercise, project/mini-project, presentation

目录页标明这些考核比例为参考值；详细考核安排以课程课纲为准。