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Literature Notes

Courses

CS224n

Lecture 1 Overview

Lecture 10 Question Answering

Lecture 11 Convolutional Neural Networks for NLP

Lecture 12 – Subword Models

Lecture 13 Contextual Word Embeddings

Lecture 14 Transformers and Self-Attention

Lecture 15 Natural Language Generation

Lecture 16 Coreference Resolution

Lecture 17 Multitasking Learning

Lecture 18 Constituency Parsing and TreeRNNs

Lecture 2 Word Vectors and Word Senses

Lecture 20 – Future of NLP + Deep Learning

Lecture 3 Word Window Classification, Neural Nets, and Calculus

Lecture 4 Back-propagation and computation graphs

Lecture 5 Dependency Parsing

Lecture 6 Language Modeling

Lecture 7 Vanishing Gradients, Fancy RNNs

Lecture 8 Translation, Seq2Seq, Attention

Lecture 9 Practical Tips for Final Projects

Lecture BERT and Other Pre-trained Language Models

CS224N NLP with Deep Learning (Winter 2019)

How to Organize your Workflow to Maximize Productivity

Mastering Productivity: Create a Custom System that Works

Course Productivity Masterclass - Principles and Tools to Boost Your Productivity

Readings [39]

Machine Learning Concepts [2]

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Privacy AI [2]

System Design [4]

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CS224n

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Lecture 1 Overview
Lecture 10 Question Answering
Lecture 11 Convolutional Neural Networks for NLP
Lecture 12 – Subword Models
Lecture 13 Contextual Word Embeddings
Lecture 14 Transformers and Self-Attention
Lecture 15 Natural Language Generation
Lecture 16 Coreference Resolution
Lecture 17 Multitasking Learning
Lecture 18 Constituency Parsing and TreeRNNs
Lecture 2 Word Vectors and Word Senses
Lecture 20 – Future of NLP + Deep Learning
Lecture 3 Word Window Classification, Neural Nets, and Calculus
Lecture 4 Back-propagation and computation graphs
Lecture 5 Dependency Parsing
Lecture 6 Language Modeling
Lecture 7 Vanishing Gradients, Fancy RNNs
Lecture 8 Translation, Seq2Seq, Attention
Lecture 9 Practical Tips for Final Projects
Lecture BERT and Other Pre-trained Language Models
CS224N NLP with Deep Learning (Winter 2019)

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