Stanford CS224N: Natural Language Processing with Deep Learning Course | Winter 2019 - Stanford CS224N: NLP with Deep Learning | Winter 2019 | Lecture 9 – Practical Tips for Projects

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3wF2RU9 Professor Christopher Manning, Stanford University http://onlinehub.stanford.edu/ Professor Christopher Manning Thomas M. Siebel Professor in Machine Learning, Professor of Linguistics and of Computer Science Director, Stanford Artificial Intelligence Laboratory (SAIL) To follow along with the course schedule and syllabus, visit: http://web.stanford.edu/class/cs224n/index.html#schedule 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