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1
Intro
2
Bag of Words
3
Algorithm Sketch
4
Tensors
5
Tensor Data Structure
6
initialization
7
uniform initialization
8
other methods
9
model
10
computation
11
operations
12
rectified linear unit
13
chain rule
14
back propagation
15
backward code
16
parameter updates
17
update sparse
18
edigrad
19
atom
20
training tricks
21
overfitting
Description:
Dive into advanced natural language processing concepts in this lecture from Carnegie Mellon University's CS 11-711 course. Explore neural networks and their toolkits, learn to define differentiable functions, and master the forward and backward algorithms. Gain insights into parameter updates and practical training techniques. Enhance your understanding of text classification through in-depth discussions on topics like bag of words, tensor data structures, initialization methods, and strategies to combat overfitting.

CMU Advanced NLP: Text Classification

Graham Neubig
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