-
Notifications
You must be signed in to change notification settings - Fork 5
/
index.html
36 lines (22 loc) · 1.25 KB
/
index.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
---
layout: lecture-home
title: Deep Neural Networks
---
<ul>
<li><b>Lecturers</b>: Prof Neil Lawrence, Dr Ferenc Huszar, Dr Nic Lane</li>
<li><b>Students</b>: Part II CST 75%</li>
<li><b>Course code</b>: DeepNN</li>
<li><b>Hours</b>: 14hrs lectures</li>
<li><b>Class limit</b>: 30</li>
</ul>
<p>There will be two assessment tasks. The first will be given out at the end of Week 3 for submisison in Week 4 (30%).
The second will be given out at the end of Week 5 for submission in Week 8 (70%).
</p>
<ul>
<li> <a href="https://www.reddit.com/r/CST_DeepNN/">Discussion forum for the module on Reddit</a>.</li>
</ul>
<h3>Lectures</h3>
<p>Details of the course lectures can be found <a href="{{ "/lectures/" | relative_url }}">here</a>.</p>
<h3>Case Studies</h3>
<p>The lectures for weeks 6 to 8 will focus on "special topics". The lectures will be given by guest lectures discussing a specific real world scenario where they have applied machine learning or machine learning would be applicable. In session 2 of week 8, we will discuss the material in light of the course and discuss potential challenges that could provide the basis for a project.</p>
<p>Details of the course case studies can be found <a href="{{ "/casestudies/" | relative_url }}">here</a>.</p>