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CS224n: Natural Language Processing with Deep Learning :fire:Study Topic
CS224n: Natural Language Processing with Deep Learning
:fire:Study Topic
[Lecture-5], 12μ 09μΌ(ν ) μμ
Backpropagation and Project Advice
https://www.youtube.com/watch?v=isPiE-DBagM&index=5&list=PL3FW7Lu3i5Jsnh1rnUwq_TcylNr7EkRe6
Suggested Readings:
ββββββ1. ββ[Vector, Matrix, and Tensor Derivatives]
ββββββββ2. Section 4 of [A Primer on Neural Network Models for Natural Language Processing]
[slides]
[Spotlight]
[paper]
[slides]
[Lecture-4], 11μ 25μΌ(ν )
Word Window Classification and Neural Networks
[slides]
[Lecture Notes 3]
https://www.youtube.com/watch?v=uc2_iwVqrRI&list=PL3FW7Lu3i5Jsnh1rnUwq_TcylNr7EkRe6&index=4
Suggested Readings
ββ2. [Review of differential calculus]
ββ3. [Natural Language Processing (almost) from Scratch]
ββββββ1. ββcs231n notes on
[backprop]
and
[network architectures]
ββββββ4. [Learning Representations by Backpropogating Errors]
[Lecture-3], 11μ 11μΌ(ν )
Advanced Word Vector Representations
[slides]
[Lecture Notes 2]
https://www.youtube.com/watch?v=ASn7ExxLZws&list=PL3FW7Lu3i5Jsnh1rnUwq_TcylNr7EkRe6&index=3
Spotlight
[slides]
[paper]
Suggested Readings
ββ2. [Improving Distributional Similarity with Lessons Learned fromWord Embeddings]
ββββββ ββ3. [Evaluation methods for unsupervised word embeddings]
ββ1. [GloVe: Global Vectors for Word Representation]
[Lecture-2], 11μ 04μΌ(ν )
Word Vector Representations: word2vec
[slides]
Spotlight
[slides]
[paper]
https://www.youtube.com/watch?v=ERibwqs9p38&list=PL3FW7Lu3i5Jsnh1rnUwq_TcylNr7EkRe6&index=2
Suggested Readings
ββ1. [Word2Vec Tutorial - The Skip-Gram Model]
2. [Distributed Representations of Words and Phrases and their Compositionality]
3. [Efficient Estimation of Word Representations in Vector Space]
[Lecture-1], 10μ 28μΌ(ν )
Introduction to NLP and Deep Learning
[Lecture Notes 1]
[python tutorial]
[slides]
Suggested Readings
2. [Probability Review]
3. [Convex Optimization Review]
1. [Linear Algebra Review]
4. [More Optimization (SGD) Review]
https://www.youtube.com/watch?v=OQQ-W_63UgQ&index=1&list=PL3FW7Lu3i5Jsnh1rnUwq_TcylNr7EkRe6
[Resource]
NLP
Neural Networks for NLP, CMU CS 11-747, Fall 2017
DeepNLP-models-Pytorch
Pytorch implementations of various Deep NLP models
in cs-224n(Stanford Univ)
reading_comprehension-cs224n
Automatic Speech Recognition β An Overview
CS224n: Natural Language Processing with Deep Learning
Oxford Deep NLP 2017 course
INF4820, Fall 2017
INF4820 - Algorithms for artificial intelligence and natural language processing, HΓΈst 2017
[Research] :pencil2:MindMap
[AI_LAB] :pencil2:MindMap
5 Best Deep Learning
in Python videos for a Beginner
Deep Learning with Keras- Python
Deep Learning with Python
Deep Learning by Andrew Ng (Full course)
TensorFlow tutorial
PyTorch Zero to All