February 2, 2020

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“Deep Learning in Natural Language Processing” - a course by DeepPavlov built on top of Stanford’s cs224n

repo name Yorko/dl_in_nlp_deeppavlov_cs224n_spring2020
repo link https://github.com/Yorko/dl_in_nlp_deeppavlov_cs224n_spring2020
language Jupyter Notebook
size (curr.) 93 kB
stars (curr.) 51
created 2020-02-04

“DL in NLP” by DeepPavlov. Spring 2020

The course is held in Russian. Main platform is this Telegram channel. Lead by Alex Sorokin (@alexeysorokin89) & Vasiliy Konovalov (@letmypeoplego), both affiliated with MIPT. Supported by OpenDataScience, unoffical discussions are held in the #class_cs224n Slack channel.

Week 1. Word Vector Representations

  1. Lectures:

  2. Quiz 1 due on Feb 10th, 9am Moscow time.

  3. Quiz 2 due on Feb 17th, 9am Moscow time.

  4. ** Assignment 1.** Github Classroom invitation link. Due on Feb 18th, 00:00 MST.

  5. Assignment 2. Studying word embeddings and implemeting word2vec. Github Classroom invitation link. Due on March 20th (extended), 23:59 Moscow time.

Weeks 2-4. Basics of neural networks

  1. Materials:

  2. Quiz 3 due on Feb 24th, 9am Moscow time.

  3. Quiz 4 due on March 2nd, 9am Moscow time.

Week 5. RNNs and language models

  1. Materials:

    • cs231n lecture 6
    • cs231n lecture 7
    • cs231n lecture notes
    • lecture on ngram models :ru:
    • “The Unreasonable Effectiveness of Recurrent Neural Networks”, a post by A. Karpathy
    • “Understanding LSTM Networks”, a post by Christopher Olah
    • On gradients in RNNs, a paper
  2. Quiz 5 due on March 9th, 9am Moscow time.

  3. Quiz 6 due on March 17th, 10am Moscow time.

Now that the official course repo is constantly updated, better to follow that one.

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