All Projects → ZacBi → Cs224n 2019 Solutions

ZacBi / Cs224n 2019 Solutions

Complete solutions for Stanford CS224n, winter, 2019

Programming Languages

python
139335 projects - #7 most used programming language

Projects that are alternatives of or similar to Cs224n 2019 Solutions

Pynlp
A pythonic wrapper for Stanford CoreNLP.
Stars: ✭ 103 (-76.38%)
Mutual labels:  stanford, natural-language-processing
Stanford Tensorflow Tutorials
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
Stars: ✭ 10,098 (+2216.06%)
Mutual labels:  stanford, natural-language-processing
Cs224n 2019
My completed implementation solutions for CS224N 2019
Stars: ✭ 178 (-59.17%)
Mutual labels:  stanford, natural-language-processing
Neuronlp2
Deep neural models for core NLP tasks (Pytorch version)
Stars: ✭ 397 (-8.94%)
Mutual labels:  natural-language-processing
Anlp19
Course repo for Applied Natural Language Processing (Spring 2019)
Stars: ✭ 402 (-7.8%)
Mutual labels:  natural-language-processing
Botlibre
An open platform for artificial intelligence, chat bots, virtual agents, social media automation, and live chat automation.
Stars: ✭ 412 (-5.5%)
Mutual labels:  natural-language-processing
Pyshorttextcategorization
Various Algorithms for Short Text Mining
Stars: ✭ 429 (-1.61%)
Mutual labels:  natural-language-processing
Dl topics
List of DL topics and resources essential for cracking interviews
Stars: ✭ 392 (-10.09%)
Mutual labels:  natural-language-processing
Bert Embedding
🔡 Token level embeddings from BERT model on mxnet and gluonnlp
Stars: ✭ 424 (-2.75%)
Mutual labels:  natural-language-processing
Cogcomp Nlp
CogComp's Natural Language Processing libraries and Demos:
Stars: ✭ 410 (-5.96%)
Mutual labels:  natural-language-processing
Portuguese Bert
Portuguese pre-trained BERT models
Stars: ✭ 409 (-6.19%)
Mutual labels:  natural-language-processing
D2l Vn
Một cuốn sách tương tác về học sâu có mã nguồn, toán và thảo luận. Đề cập đến nhiều framework phổ biến (TensorFlow, Pytorch & MXNet) và được sử dụng tại 175 trường Đại học.
Stars: ✭ 402 (-7.8%)
Mutual labels:  natural-language-processing
Dialogflow Javascript Client
JavaScript Web SDK for Dialogflow
Stars: ✭ 416 (-4.59%)
Mutual labels:  natural-language-processing
Projects
🪐 End-to-end NLP workflows from prototype to production
Stars: ✭ 397 (-8.94%)
Mutual labels:  natural-language-processing
Ernie
Official implementations for various pre-training models of ERNIE-family, covering topics of Language Understanding & Generation, Multimodal Understanding & Generation, and beyond.
Stars: ✭ 4,659 (+968.58%)
Mutual labels:  natural-language-processing
Sherlock
Natural-language event parser for Javascript
Stars: ✭ 393 (-9.86%)
Mutual labels:  natural-language-processing
Deep Learning Nlp
📡 Organized Resources for Deep Learning in Natural Language Processing
Stars: ✭ 421 (-3.44%)
Mutual labels:  natural-language-processing
Reductio
Automatic summarizer text in Swift
Stars: ✭ 406 (-6.88%)
Mutual labels:  natural-language-processing
Gnn4nlp Papers
A list of recent papers about Graph Neural Network methods applied in NLP areas.
Stars: ✭ 405 (-7.11%)
Mutual labels:  natural-language-processing
Mlinterview
A curated awesome list of AI Startups in India & Machine Learning Interview Guide. Feel free to contribute!
Stars: ✭ 410 (-5.96%)
Mutual labels:  natural-language-processing

996.icu

CS224n-winter19

Solutions for CS224n, winter, 2019.
Welcome to discuss problems appearing in assigments, please submit to issue.
Also take notes for the key point in lectures. The solutions for assignment is written by Markdown in Assignments/written part.  


Update

update 2019/12/03

  After CS224n I realize that more systematical training is needed. So I start a new repo learn_NLP_again, here is the description(algorithms and solutions is available for chapter 1 until now):

  Here is why I started this project: learn NLP from scratch again. I choose Speech and language process as my entry point, and try to write solutions and implement some algorithms/models of this book. I hope I can stick to this project and update frequently.

  After one year's training in corporation and lab, I find many faults or incorrect habbits in past parctice, (btw, there is too many commits in this repo). I'll review the code in this repo and solve issues gradually.(😄, hopefully)

Welcome communications in new repo!

w1

reading

  • [x] note: Word Vectors I: Introduction, SVD and Word2Ve
  • [x] Word2Vec Tutorial - The Skip-Gram Model  

practice

  • [x] coding: Assignment1
  • [x] Gensim

w2

reading

  • [x] note: Word Vectors II: GloVe, Evaluation and Trainin
  • [x] gradient-notes
  • [x] CS231n notes on backprop
  • [x] review-differential-calculus
  • [x] backprop_old
  • [x] CS231n notes on network architectures

practice

  • [x] coding: Assignment2
  • [x] writing: Assignment2

w3

reading

  • [x] note: Dependency Parsing
  • [x] note: Language Models and Recurrent Neural Network
  • [x] a3

practice

  • [x] coding: Assignment3
  • [x] writing: Assignment3

w4

reading

  • [x] note: Machine Translation, Sequence-to-sequence and Attention
  • [x] a4
  • [x] read: Attention and Augmented Recurrent Neural Networks
  • [x] read: Massive Exploration of Neural Machine Translation Architectures (practical advice for hyperparameter choices)

practice

  • [x] coding: Assignment4
  • [x] writing: Assignment4

key point for a4

How to understand pack_padded_sequence and pad_packed_sequence?
(Chinese ed)
(English ed)

w5

It has been long time for no updating...

reading

  • [x] note: Machine Translation, Sequence-to-sequence and Attention
  • [x] a4
  • [x] read: Attention and Augmented Recurrent Neural Networks

practice

  • [x] coding: Assignment5
  • [x] writing: Assignment5

Final project

reading:

  • [x] final-project-practical-tips
  • [x] default-final-project-handout
  • [x] project-proposal-instructions
  • [x] Practical Methodology_Deep Learning book chapter
  • [x] Highway Networks
  • [x] Bidirectional Attention Flow for Machine Comprehension

practice:

  • [x] anotate codes
  • [x] train baseline
Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].