
모두를 위한 대규모 언어 모델 LLM Part 5 - LangGraph로 나만의 AI 에이전트 만들기
AISchool
최신 AI 기술의 총집합체인 AI 에이전트! 다양한 AI 에이전트들을 구현해보면서 LangGraph를 이용한 나만의 AI 에이전트 구현법을 학습해봅니다.
Intermediate
LangGraph, AI Agent, LangChain
A course to learn deep learning paper implementation skills, implementing the GPT-1 (Improving Language Understanding by Generative Pre-Training) paper from scratch with TensorFlow 2.0.
How to Read Deep Learning Papers
How to implement Deep Learning papers
Detailed Understanding of GPT (Generative Pre-trained Transformer) Model Structure
GPT (Generative Pre-trained Transformer) Model Background
Coding with TensorFlow 2.0
An essential skill for deep learning researchers: the ability to implement the latest research papers!
Learn with GPT implementation 😀
When hiring deep learning researchers, many companies give preference to those with experience implementing the latest papers .
Gain experience implementing the latest papers by implementing the GPT-1 (Improving Language Understanding by Generative Pre-Training) paper yourself.
We will read the GPT-1 paper (Improving Language Understanding by Generative Pre-Training) and implement the GPT-1 model from scratch using TensorFlow 2.0 .
👋 This course requires prior knowledge of TensorFlow 2.0 and natural language processing (NLP) . Be sure to take the courses below first or have equivalent knowledge before taking this course.
Q. What are the benefits of experiencing implementing deep learning papers?
Who is this course right for?
Those wishing to develop deep learning paper reading and implementation skills.
Individuals aspiring to deep learning research roles.
Those who wish to conduct AI/Deep Learning research
AI Graduate School Preparers
Need to know before starting?
Python experience
Prior Course: [Introduction to Deep Learning Natural Language Processing with Examples: NLP with TensorFlow - From RNN to BERT] Course Experience
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30 lectures ∙ (4hr 27min)
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$84.70
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