Natural Language Processing

Natural Language Processing Machine Learning, Deep Learning

Natural Language Processing

Prompt-Based Learning 3 | P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks 13 Jan 2023

Prompt-Based Learning 2 | P-tuniung: GPT Understands, Too 21 Dec 2022

Prompt-Based Learning 1 | PET(Pattern Exploiting Training), iPET(Iterative Pattern Exploiting Training) 15 Dec 2022

Language Models Summary(unfinished post) 30 Nov 2022

DAPT-TAPT | Don’t Stop Pretraining: Adapt Language Models to Domains and Tasks 29 Nov 2022

BERT | Pre-training of Deep Bidirectional Transformers for Language Understanding 22 Nov 2019

Transformer | Attention Is All You Need 19 Nov 2019

Attention in sequence to sequence 12 Nov 2019

Sequence to Sequence(Seq2Seq) 11 Nov 2019

GloVe(Global Word Vectors) 07 Nov 2019

FastText | Enriching Word Vectors with Subword Information 07 Nov 2019

Word2vec | Skip-gram 06 Nov 2019

Word2Vec(Sentimental Categorize);with code 06 Nov 2019

Word2vec | CBOW(Continuous Bag Of Words Model) 05 Nov 2019

NPLM(Neural Probabilistic Language Model) 04 Nov 2019

Word embedding(Distributed Representation) 03 Nov 2019

LSA(Latent Sematic Analysis) 03 Nov 2019

How to represent words?( Word Vectors) 01 Nov 2019

Tokenization;with code 31 Oct 2019

Regular Expression;with code 31 Oct 2019

NLP Basics;with code 31 Oct 2019

What is Natural Language Processing(NLP)? 30 Oct 2019

Machine Learning, Deep Learning

Linear Regression;with code 07 Aug 2021

K-Means;with code 03 Aug 2021

L1, L2 (Norm, Loss, Regularization) 04 Oct 2020

Transfer Learning, Multi-task Learning, End-to-End deep learning 01 Oct 2020