Core Principles Agent AI, Machine Learning, and NLP: Origins, Relationships, and Taxonomy Understanding the Blackjack Value Function — Notes on Sutton & Barto Figure 5.1 Does DP Always Need Probabilities? A Look at DP vs. Monte Carlo in Reinforcement Learning Is the Convergence of Monte Carlo ES Still an Open Problem?Data Process Datasets Embedding模型的内部机制详解长文本信息稀释原因及可能方向 Understanding Information Retrieval Evaluation Metrics: NDCG, MAP, and MRR Fixing PyTorch dtype Mismatch: Long vs Float in Matrix Multiplication Understanding NDCG Evaluation with ranx LiteLLM: More Than Just a Router MCP Memory Mixture of Experts (MoE): Scalable Machine Learning Architecture Monte Carlo Methods in Reinforcement Learning: A Deep Dive From MNIST to Full-Document OCR: Bridging the Gap Between CNN Classification and Real-World Text Recognition LiteLLM, Ollama, and vLLM: Understanding Model Switching at Every Layer Optimum Players Products Pytorch RAG RL Why Perplexity Rises at the Start of RNN Training Skill Usages Table Understanding with RAG Template Why np.array Breaks Autograd Backpropagation: A Subtle Python Reference Bug Transformers Utilities Explicit vs. Implicit Features: What Every Software Architect Must Consider “扛责”Why sh -c "cd dir && pwd" Prints the Wrong Directory Chromadb Python Package MinIO Mirror and Backup: A Practical Guide to mc mirror --watch MinIO: Why Object Storage Beats a Plain Directory Structure PostgreSQL vs SQLite ChromaDB Python Package File Management in Linux: file and ls Github Pages Tensor Azure Proxy backend/open_webui/utils/middleware.py Deep Dive: RAGFlow’s Admin & Superuser Initialization System How RAGflow’s APIToken.query Works Under the Hood Understanding RAGflow’s api_token Table Deep Dive: RAGFlow’s Document Parsing Pipeline How RAGflow Uses operator.attrgetter for Lazy ORM Query Building Building Q&A with ragflow_sdk: Chat, Session, and ask()From Elasticsearch Queries to Kubernetes Cluster Deployment: A RAGFlow Journey How RAGFlow Creates a Dataset: A Code Walkthrough Where Does a Dataset Actually Live in RAGFlow?Upload Is Not Enough: Understanding RAGFlow’s Two-Step Document Processing Pipeline How RAGFlow Generates Knowledge Graphs and RAPTOR Hierarchies Important tables How RAGFlow Resolves index_name and knowledgebase_id During Chat Why Infinity Is a Strong Document Engine for RAGFlow How RAGflow Bootstraps a Knowledge Base: Inside init_kb and create_idx How RAGFlow Handles User Invitations and Multi-Tenant Access Control kb/create and /datasets How RAGFlow Creates and Persists a Knowledge Base: A Service-Layer Walkthrough How RAGFlow Handles Passwords: Transport Encryption + One-Way Hashing Studied code Why User ID Equals Tenant ID in RAGFlow: A Practical Multi-Tenant Design RAGFlow Search Flow: A Deep Dive into the Retrieval Pipeline Deep Dive into RAGFlow’s Search Architecture: Document Storage, Hybrid Retrieval, and Similarity Computation How RAGFlow Stores Files in MinIO Deep Dive into RAGFlow’s Task Executor: How Asynchronous Document Processing Works Inside RAGFlow User Management: A Practical Look at the user Table Converting HTML to PDF in Python: A Complete Guide Scrapy: Why custom_settings on Your Spider Gets Ignored Scrapy: Spider.parse → ItemPipeline → New Request Flow Handling Pages That Require Login with Playwright Handling Large Tables When Converting Web Pages to PDF with Playwright Scrapy Log Saving Saving Scraped Data to a Database in Scrapy Secure Secret Input: How to Read Sensitive Data Without Exposing It useradd VS adduser SSH (Secure Shell)FastAPI 本地 Uvicorn + FastAPI 获取 IP NGINX Learn Artificial Intelligence Building Better Neural Networks: ReLU and Dropout in a Three-Layer Architecture 架构师 Bash Compiler Container Database Disk Documentation Mermaid Edk2 Flutter Github GPU Invest Langchain Mathematics Microsoft NEO4j Network numpy Open-WebUI Python RAG Flow Research Robot Natural Science Scrapy Security Share Universities Video VIM VNC Visual Code Weights & Biases Web X Window

Data Process

Data Process

import pandas as pd
pd.DataFrame()

Learning

Learning

Record learning from practice