Stanford CS224N: NLP with Deep Learning | Winter 2019 | Lecture 9 – Practical Tips for Projects

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Professor Christopher Manning, Stanford University

Professor Christopher Manning
Thomas M. Siebel Professor in Machine Learning, Professor of Linguistics and of Computer Science
Director, Stanford Artificial Intelligence Laboratory (SAIL)

0:00 Introduction
0:20 Lecture Plan
3:38 Mid-quarter feedback survey
4:09 1. Course work and grading policy
4:19 The Final Project
10:48 Why Choose The Default Final Project?
13:15 Why Choose The Custom Final Project?
15:34 Project Proposal - from everyone 5%
17:22 Project Milestone - from everyone 5%
18:15 Finding Research Topics
19:16 Project types
30:45 Must-haves (for most custom final projects)
31:58 Finding data
33:30 Linguistic Data Consortium
34:25 Machine translation
35:10 Dependency parsing: Universal Dependencies
36:37 One more look at gated recurrent
38:29 Gated Recurrent Unit
51:05 The large output vocabulary
54:17 The word generation problem
55:45 Possible approaches for output
59:11 MT Evaluation - an example of eval

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