New Books

File	Tags
330.20 c	#Applications, #Backend, #Discord_AI_Bot_Development_Best_Post_Recommendation, #Discord_베스트_포스트_추천_봇_만들기_시리즈_2편_Mock데이터로_10008에러_데이터도_수집하기_그_와중에_또다시_발생한_모든메시지0인_예외_케이스
330.20 a	#Applications, #Backend, #Discord_AI_Bot_Development_Best_Post_Recommendation, #Discord_베스트_포스트_추천_봇_만들기_시리즈
330.20 f	#Applications, #Backend, #Discord_AI_Bot_Development_Best_Post_Recommendation, #Discord_베스트_포스트_추천_봇_만들기_시리즈_5편_클라우드와_크론잡을_통해_24시간_서비스_생성하기
330.20 e	#Applications, #Backend, #Discord_AI_Bot_Development_Best_Post_Recommendation, #Discord_베스트_포스트_추천_봇_만들기_시리즈_4편_프로덕션_올리기전_시크릿_제거하기_bfg-repo-cleaner
330.20 d	#Applications, #Backend, #Discord_AI_Bot_Development_Best_Post_Recommendation, #Discord_베스트_포스트_추천_봇_만들기_시리즈_3편_파일_읽기_쓰기와_디스코드_봇_커맨드_구현하기

External Resources

Categories Lists

Call Number Index

000 IT Knowledge
- 010 Develop Knowledge
  - 010.00 Develop Computer Science Knowledge
    - 010.00 b SLA and SLO and SLI
  - 010.10 Data Structure and Algorithm
    - 010.10 a Why learn data structures and algorithms?
    - 010.10 b Datastructure overview
  - 010.20 Diagram UML
    - 010.20 a UML Diagrams
- 020 Operation Knowledge
  - 020.00 Versioning
    - 020.00 a My own Versioning Strategy
    - 020.00 b headver
    - 020.00 c Proper dividing for reusable modules
  - 020.10 Git
    - 020.10 a Git Command Usecases git 명령어 실전 사용 및 응용 편
- 030 Package
  - 030.00 PIP
    - 030.00 a pip name and module name
- 090 External Insights
  - 090.00 Publications
    - 090.00 a Developer Trivia, Things You Should Have Known Before You Became a Developer
  - 090.10 Activity
    - 090.10 a Naver boostcamp Basic
    - 090.10 b 우아한테크코스 1주차 회고록
100 Infra
- 110 DevOps Engineer Infra
  - 110.00 Docker
    - 110.00 a Simple docker command things
    - 110.00 b Docker credential credsStore with Kaniko
    - 110.00 c Multi stage builds
  - 110.10 Kubernetes
    - 110.10 a Kops script for installing GitLab
    - 110.10 b eksctl commands
    - 110.10 c Helm
    - 110.10 d Helm Argocd Ingress trouble shooting AWS EKS
    - 110.10 e Loki with Helm
    - 110.10 f What to do if password settings don't work well in Grafana helm charts
- 120 ML Engineer Infra
  - 120.00 GPU
    - 120.00 a How to easily rent an expensive GPU and what to consider when choosing one
200 DevOps
- 210 CICD
  - 210.00 DevOps Fundamental
    - 210.00 a DevOps Background
- 220 Project Management System
  - 220.10 PMS in Action Implementation
    - 220.10 a GitLab Issue template
300 Applications
- 310 Development Environment
  - 310.10 Conda
    - 310.10 a Conda base
    - 310.10 b Conda License
  - 310.20 Debugger
    - 310.20 a BreakPoint
- 320 Frontend
  - 320.00 HTML
    - 320.00 a Think about HTML
  - 320.10 CSS
    - 320.10 a CSS Default
  - 320.30 JavaScript
    - 320.30 a JavaScript import export 모듈 관련 예제와 함께 알아보기
    - 320.30 b Fix too loud sound at video startup with headphones on
    - 320.30 c Jest 관련 JavaScript에서의 테스트 개요
- 330 Backend
  - 330.00 Django
    - 330.00 a Django default project
    - 330.00 b Difference between Django and FastAPI
  - 330.10 Node.js
    - 330.10 a Variable Specification
    - 330.10 b async, await and promise
  - 330.20 Discord AI Bot Development Best Post Recommendation
    - 330.20 a Discord 베스트 포스트 추천 봇 만들기 시리즈
    - 330.20 b Discord 베스트 포스트 추천 봇 만들기 시리즈 1편 프로덕션환경에서 기존 기능 수행하기 (feat들어본적도 없는 10008에러 해결)
    - 330.20 c Discord 베스트 포스트 추천 봇 만들기 시리즈 2편 Mock데이터로 10008에러 데이터도 수집하기 그 와중에 또다시 발생한 모든메시지0인 예외 케이스
    - 330.20 d Discord 베스트 포스트 추천 봇 만들기 시리즈 3편 파일 읽기 쓰기와 디스코드 봇 커맨드 구현하기
    - 330.20 e Discord 베스트 포스트 추천 봇 만들기 시리즈 4편 프로덕션 올리기전 시크릿 제거하기 bfg-repo-cleaner. 그 와중 커밋이 2배로 늘어나버린 경우
    - 330.20 f Discord 베스트 포스트 추천 봇 만들기 시리즈 5편 클라우드와 크론잡을 통해 24시간 서비스 생성하기
400 ML Engineer Basic
- 410 Mathematics
  - 410.00 Linear Algebra
    - 410.00 a Vectors Properties
    - 410.00 b Vector Operation
  - 410.10 Probability
    - 410.10 a Fundamental Words
  - 410.20 Statistics
    - 410.20 a Probability Distribution and Estimation
    - 410.20 b Maximum Likelihood Estimation(MLE) and Deep Learning
  - 410.30 Calculus
    - 410.30 a Fundamental Calculus
- 420 Data
  - 420.00 Structured Data
    - 420.00 a Numerical Data (Continuous and Discrete)
    - 420.00 b Categorical Data (Ordinal and Nominal)
- 430 ML Development Tools
  - 430.00 LangChain
    - 430.00 a Langchain Components
    - 430.00 b Amazon_Bedrock_with_RAG
    - 430.00 c RAG_with_FAISS
  - 430.10 Streamlit
    - 430.10 a LLM RAG Application Using Langchain and FAISS
  - 430.20 Gradio
    - 430.20 a Gradio Quick Tutorial
- 440 ML Methodology
  - 440.00 EDA(Exploratory Data Analysis)
    - 440.00 a Initiating Exploratory Data Analysis
500 ML and DL Modeling
- 520 Computer Vision
  - 520.00 Introduction to CV
    - 520.00 a Voxelization from Open3D Library
600 ML Libraries and Implementation
- 610 Data Handling
  - 610.00 Pandas
    - 610.00 a Pandas-basic
  - 610.10 NumPy
    - 610.10 a Numpy Fundamental functions
- 620 Data visualization
  - 620.00 Matplotlib
    - 620.00 a Matplotlib Fundamental
  - 620.10 Seaborn
    - 620.10 a Seaborn Fundamental
  - 620.20 Script
    - 620.20 a Shell Scirpt For visualize GPU usage
- 630 Machine Learning Frameworks
  - 630.00 scikit-learn
    - 630.00 a scikit-learn functions
  - 630.50 LlamaIndex
    - 630.50 a RAPTOR RAG
- 640 Vector Database
  - 640.00 VectorDB Solutions
- 650 Prompt Engineering
  - 650.00 Prompt Use case
    - 650.00 a Qr Code Color Placement Recommendation with Design
    - 650.00 b When AI doesn't know where up and down are, use text to represent them
  - 650.10 Prompt Theory
    - 650.10 a Checklist for Prompt Engineering
700 Research Paper
- 710 methodology
  - 710.00 Multi-agent Reinforcement Learning
    - 710.00 a Base Domains
    - 710.00 b Mindcraft
    - 710.00 c Creative-Agents
- 720 Computer Vision
  - 720.00 3D Generation
    - 720.00 a DREAMGAUSSIAN: GENERATIVE GAUSSIAN SPLATTING FOR EFFICIENT 3D CONTENT CREATION
  - 720.10 Text to 3D
    - 720.10 a ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation
    - 720.10 b GaussianDreamer: Fast Generation from Text to 3D Gaussians by Bridging 2D and 3D Diffusion Models
  - 720.20 3D Reconstruction
    - 720.20 c Triplane Meets Gaussian Splatting: Fast and Generalizable Single-View 3D Reconstruction with Transformers
800 Anythings
- 810 Game
  - 810.00 Minecraft
    - 810.00 a Minecraft Commands
- 820 Writing
  - 820.00 LinkedIn
    - 820.00 a Why I Use Obsidian as KnowldegeBase Tool
    - 820.00 b Year 1 Review What I Learned at the Company
- 830 Hobby
  - 830.00 3D Works
    - 830.00 a 3D object domain knowledge
900 Life Lessons
- 910 Self Discoveries
  - 910.00 Approach to Life
    - 910.00 a Hodie Vixi(Today I Lived)
    - 910.00 b How you can try something you've given up on as impossible
    - 910.00 c Digital Detox Learning from a Failure to Detox
    - 910.00 d Methods to use metrics to evaluate which job is better
    - 910.00 e Don't miss the moment when their eyes sparkle if you want to catch someone or keep them for a long timeN

History of Library

Link: History of Library