Tag: #nlp

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• [Deep RL] 12. Training Chatbots with Reinforcement Learning

  Combining Seq2Seq models with reinforcement learning for chatbot training: from RNN basics to Self-Critical Sequence Training (SCST)

  2026-03-19 · 7 min read #reinforcement-learning#deep-learning#ai#nlp

• Complete Guide to Korean NLP and LLM: Mastering KoBERT, KLUE, HyperCLOVA, and EXAONE

  A comprehensive guide to Korean NLP and LLM covering KoBERT, KLUE, HyperCLOVA, and EXAONE.

  2026-03-17 · 27 min read #korean-nlp#kobert#klue#hyperclova#exaone

• Transformer Architecture Complete Analysis: From Attention to Modern LLMs

  A complete guide to understanding Transformer architecture from scratch. Covers Self-Attention, Multi-Head Attention, Positional Encoding, and Encoder-Decoder structure through Flash Attention, RoPE, and GQA with formula

  2026-03-17 · 22 min read #transformer#attention#deep-learning#nlp#ai

• NLP & Text Processing Complete Guide: BERT Fine-tuning, RAG Systems, and Multilingual Processing

  A comprehensive guide to NLP and text processing covering BPE tokenization, Word2Vec, BERT fine-tuning, RAG pipelines, and Korean morpheme analysis.

  2026-03-17 · 15 min read #nlp#bert#embeddings#rag#koreannlp

• Natural Language Processing Complete Guide: Zero to Hero - From Text Processing to LLMs

  A comprehensive guide from NLP fundamentals to the latest LLMs. Learn text preprocessing, Word2Vec, RNN/LSTM, Attention, Transformer, BERT, and GPT step by step with practical code examples.

  2026-03-17 · 33 min read #nlp#natural-language-processing#transformer#bert#gpt

• HuggingFace Ecosystem Complete Guide: Master Transformers, Datasets, PEFT, and Accelerate

  A complete guide to mastering the entire HuggingFace ecosystem. Learn Transformers, Datasets, Tokenizers, PEFT, Accelerate, Diffusers, and Hub API with hands-on examples.

  2026-03-17 · 18 min read #huggingface#transformers#peft#accelerate#nlp

• RAG Paper Survey: The Evolution of Retrieval-Augmented Generation — From RETRO to Self-RAG and Corrective-RAG

  Traces the evolution of RAG research through papers. Compares architectures and benchmarks from the original RAG to RETRO large-scale retrieval, Self-RAG self-reflection, and Corrective-RAG retrieval quality evaluation.

  2026-03-12 · 22 min read #ai-papers#rag#self-rag#corrective-rag#retro

• Complete Analysis of the BERT Paper: How Bidirectional Transformers Changed the Landscape of NLP

  An in-depth analysis of Google BERT paper. We cover bidirectional pre-training through Masked Language Model (MLM) and Next Sentence Prediction (NSP), fine-tuning strategies, and the core principles of the architecture t

  2026-03-01 · 28 min read #bert#nlp#transformer#pre-training#fine-tuning

• Running KoGPT

  Running KoGPT

  2023-01-17 · 3 min read #nlp