The complete archive

The complete archive

Every piece, by year — newest at the top.

2026

Mar 26 Terraform for AI Agents (8): End-to-End — research-agent-stack in One Apply Terraform Agents

Mar 24 Terraform for AI Agents (7): Observability, SLS Dashboards, and Cost Alarms Terraform Agents

Mar 22 Terraform for AI Agents (6): LLM Gateway and Secrets Management Terraform Agents

Mar 20 Terraform for AI Agents (5): Storage — Vector, Relational, and Object Memory Terraform Agents

Mar 18 Terraform for AI Agents (4): Compute — ECS, ACK, or Function Compute? Terraform Agents

Mar 16 Terraform for AI Agents (3): A Reusable VPC and Security Baseline Terraform Agents

Mar 14 Terraform for AI Agents (2): Provider, Auth, and Remote State on OSS Terraform Agents

Mar 12 Terraform for AI Agents (1): Why IaC Is the Only Sane Way to Ship Agents Terraform Agents

Mar 09 Aliyun PAI (5): Designer vs Model Gallery — When the GUIs Actually Earn Their Keep Aliyun PAI

Mar 08 Aliyun PAI (4): PAI-EAS — Model Serving, Cold Starts, and the TPS Lie Aliyun PAI

Mar 07 Aliyun PAI (3): PAI-DLC — Distributed Training Without the Cluster Pain Aliyun PAI

Mar 06 Aliyun PAI (2): PAI-DSW — Notebooks That Don't Eat Your Weights Aliyun PAI

Mar 05 Aliyun PAI (1): Platform Overview and the Product Family Map Aliyun PAI

Mar 01 Aliyun Bailian (5): Qwen-TTS for Multilingual Voice Aliyun Bailian

Feb 28 Aliyun Bailian (4): Wanxiang Video Generation End-to-End Aliyun Bailian

Feb 27 Aliyun Bailian (3): Qwen-Omni for Video, Audio, and Image Understanding Aliyun Bailian

Feb 26 Aliyun Bailian (2): The Qwen LLM API in Production Aliyun Bailian

Feb 25 Aliyun Bailian (1): Platform Overview and First Request Aliyun Bailian

Feb 08 ML Math Derivations (20): Regularization and Model Selection ML Math Derivations

Feb 07 ML Math Derivations (19): Neural Networks and Backpropagation ML Math Derivations

Feb 06 ML Math Derivations (18): Clustering Algorithms ML Math Derivations

Feb 05 ML Math Derivations (17): Dimensionality Reduction and PCA ML Math Derivations

Feb 04 ML Math Derivations (16): Conditional Random Fields ML Math Derivations

Feb 03 Machine Learning Mathematical Derivations (15): Hidden Markov Models ML Math Derivations

Feb 02 Machine Learning Mathematical Derivations (14): Variational Inference and Variational EM ML Math Derivations

Feb 01 Machine Learning Mathematical Derivations (13): EM Algorithm and GMM ML Math Derivations

Jan 31 Machine Learning Mathematical Derivations (12): XGBoost and LightGBM ML Math Derivations

Jan 30 Machine Learning Mathematical Derivations (11): Ensemble Learning ML Math Derivations

Jan 29 Machine Learning Mathematical Derivations (10): Semi-Naive Bayes and Bayesian Networks ML Math Derivations

Jan 28 Machine Learning Mathematical Derivations (9): Naive Bayes ML Math Derivations

Jan 27 Machine Learning Mathematical Derivations (8): Support Vector Machines ML Math Derivations

Jan 26 Machine Learning Mathematical Derivations (7): Decision Trees ML Math Derivations

Jan 25 Machine Learning Mathematical Derivations (6): Logistic Regression and Classification ML Math Derivations

Jan 24 Mathematical Derivation of Machine Learning (5): Linear Regression ML Math Derivations

Jan 23 ML Math Derivations (4): Convex Optimization Theory ML Math Derivations

Jan 22 ML Math Derivations (3): Probability Theory and Statistical Inference ML Math Derivations

Jan 21 Solving Constrained Mean-Variance Portfolio Optimization Using Spiral Optimization Standalone

Jan 21 ML Math Derivations (2): Linear Algebra and Matrix Theory ML Math Derivations

Jan 20 ML Math Derivations (1): Introduction and Mathematical Foundations ML Math Derivations

Jan 15 Recommendation Systems (16): Industrial Architecture and Best Practices Recommendation Systems

Jan 12 Recommendation Systems (15): Real-Time Recommendation and Online Learning Recommendation Systems

Jan 09 Recommendation Systems (14): Cross-Domain Recommendation and Cold-Start Solutions Recommendation Systems

Jan 06 Recommendation Systems (13): Fairness, Debiasing, and Explainability Recommendation Systems

Jan 03 Recommendation Systems (12): Large Language Models and Recommendation Recommendation Systems

2025

Dec 31 Recommendation Systems (11): Contrastive Learning and Self-Supervised Learning Recommendation Systems

Dec 31 AI Agents Complete Guide: From Theory to Industrial Practice Standalone

Dec 28 Recommendation Systems (10): Deep Interest Networks and Attention Mechanisms Recommendation Systems

Dec 25 Recommendation Systems (9): Multi-Task Learning and Multi-Objective Optimization Recommendation Systems

Dec 22 Recommendation Systems (8): Knowledge Graph-Enhanced Recommendation Recommendation Systems

Dec 19 Recommendation Systems (7): Graph Neural Networks and Social Recommendation Recommendation Systems

Dec 16 Recommendation Systems (6): Sequential Recommendation and Session-based Modeling Recommendation Systems

Dec 13 Recommendation Systems (5): Embedding and Representation Learning Recommendation Systems

Dec 10 Recommendation Systems (4): CTR Prediction and Click-Through Rate Modeling Recommendation Systems

Dec 07 Recommendation Systems (3): Deep Learning Foundations Recommendation Systems

Dec 04 Recommendation Systems (2): Collaborative Filtering and Matrix Factorization Recommendation Systems

Dec 01 Recommendation Systems (1): Fundamentals and Core Concepts Recommendation Systems

Nov 25 NLP (12): Frontiers and Practical Applications NLP

Nov 20 NLP (11): Multimodal Large Language Models NLP

Nov 15 NLP (10): RAG and Knowledge Enhancement Systems NLP

Nov 10 NLP (9): Deep Dive into LLM Architecture NLP

Nov 05 NLP (8): Model Fine-tuning and PEFT NLP

Oct 31 NLP (7): Prompt Engineering and In-Context Learning NLP

Oct 26 NLP Part 6: GPT and Generative Language Models NLP

Oct 21 NLP Part 5: BERT and Pretrained Models NLP

Oct 16 NLP Part 4: Attention Mechanism and Transformer NLP

Oct 15 Prompt Engineering Complete Guide: From Zero to Advanced Optimization Standalone

Oct 11 NLP Part 3: RNN and Sequence Modeling NLP

Oct 06 NLP Part 2: Word Embeddings and Language Models NLP

Oct 01 NLP Part 1: Introduction and Text Preprocessing NLP

Sep 25 Reinforcement Learning (12): RLHF and LLM Applications Reinforcement Learning

Sep 22 Low-Rank Matrix Approximation and the Pseudoinverse: From SVD to Regularization Standalone

Sep 20 Reinforcement Learning (11): Hierarchical RL and Meta-Learning Reinforcement Learning

Sep 15 Reinforcement Learning (10): Offline Reinforcement Learning Reinforcement Learning

Sep 10 Reinforcement Learning (9): Multi-Agent Reinforcement Learning Reinforcement Learning

Sep 05 Reinforcement Learning (8): AlphaGo and Monte Carlo Tree Search Reinforcement Learning

Aug 31 Reinforcement Learning (7): Imitation Learning and Inverse RL Reinforcement Learning

Aug 26 Reinforcement Learning (6): PPO and TRPO -- Trust Region Policy Optimization Reinforcement Learning

Aug 21 Reinforcement Learning (5): Model-Based RL and World Models Reinforcement Learning

Aug 16 Reinforcement Learning (4): Exploration Strategies and Curiosity-Driven Learning Reinforcement Learning

Aug 11 Reinforcement Learning (3): Policy Gradient and Actor-Critic Methods Reinforcement Learning

Aug 06 Reinforcement Learning (2): Q-Learning and Deep Q-Networks (DQN) Reinforcement Learning

Aug 01 Reinforcement Learning (1): Fundamentals and Core Concepts Reinforcement Learning

Jul 24 Reparameterization Trick & Gumbel-Softmax: A Deep Dive Standalone

Jul 06 Transfer Learning (12): Industrial Applications and Best Practices Transfer Learning

Jun 30 Transfer Learning (11): Cross-Lingual Transfer Transfer Learning

Jun 24 Transfer Learning (10): Continual Learning Transfer Learning

Jun 21 Symplectic Geometry and Structure-Preserving Neural Networks Standalone

Jun 21 LLM Workflows and Application Architecture: Enterprise Implementation Guide Standalone

Jun 18 Transfer Learning (9): Parameter-Efficient Fine-Tuning Transfer Learning

Jun 12 Transfer Learning (8): Multimodal Transfer Transfer Learning

Jun 06 Transfer Learning (7): Zero-Shot Learning Transfer Learning

May 31 Transfer Learning (6): Multi-Task Learning Transfer Learning

May 25 Transfer Learning (5): Knowledge Distillation Transfer Learning

May 19 Transfer Learning (4): Few-Shot Learning Transfer Learning

May 13 Transfer Learning (3): Domain Adaptation Transfer Learning

May 07 Transfer Learning (2): Pre-training and Fine-tuning Transfer Learning

May 01 Transfer Learning (1): Fundamentals and Core Concepts Transfer Learning

Apr 30 Essence of Linear Algebra (18): Frontiers and Summary Linear Algebra

Apr 23 Essence of Linear Algebra (17): Linear Algebra in Computer Vision Linear Algebra

Apr 16 Essence of Linear Algebra (16): Linear Algebra in Deep Learning Linear Algebra

Apr 09 Essence of Linear Algebra (15): Linear Algebra in Machine Learning Linear Algebra

Apr 02 Essence of Linear Algebra (14): Random Matrix Theory Linear Algebra

Mar 31 Prefix-Tuning: Optimizing Continuous Prompts for Generation Standalone

Mar 26 Essence of Linear Algebra (13): Tensors and Multilinear Algebra Linear Algebra

Mar 19 Sparse Matrices and Compressed Sensing -- Less Is More Linear Algebra

Mar 12 Matrix Calculus and Optimization -- The Engine Behind Machine Learning Linear Algebra

Mar 05 Matrix Norms and Condition Numbers -- Is Your Linear System Healthy? Linear Algebra

Feb 26 Singular Value Decomposition -- The Crown Jewel of Linear Algebra Linear Algebra

Feb 19 Symmetric Matrices and Quadratic Forms -- The Best Matrices in Town Linear Algebra

Feb 12 Orthogonality and Projections -- When Vectors Mind Their Own Business Linear Algebra

Feb 05 Eigenvalues and Eigenvectors Linear Algebra

Jan 29 Linear Systems and Column Space Linear Algebra

Jan 22 The Secrets of Determinants Linear Algebra

Jan 15 Matrices as Linear Transformations Linear Algebra

Jan 08 Linear Combinations and Vector Spaces Linear Algebra

Jan 01 The Essence of Vectors -- More Than Just Arrows Linear Algebra

2024

Dec 15 Time Series Forecasting (8): Informer -- Efficient Long-Sequence Forecasting Time Series Forecasting

Dec 06 Vim Essentials: Modal Editing, Motions, and a Repeatable Workflow Standalone

Nov 30 Time Series Forecasting (7): N-BEATS -- Interpretable Deep Architecture Time Series Forecasting

Nov 15 Time Series Forecasting (6): Temporal Convolutional Networks (TCN) Time Series Forecasting

Oct 31 Time Series Forecasting (5): Transformer Architecture for Time Series Time Series Forecasting

Oct 16 Time Series Forecasting (4): Attention Mechanisms -- Direct Long-Range Dependencies Time Series Forecasting

Oct 12 MoSLoRA: Mixture-of-Subspaces in Low-Rank Adaptation Standalone

Oct 07 Tennis-Scene Computer Vision: From Paper Survey to Production Standalone

Oct 01 Time Series Forecasting (3): GRU -- Lightweight Gates and Efficiency Trade-offs Time Series Forecasting

Sep 16 Time Series Forecasting (2): LSTM -- Gate Mechanisms and Long-Term Dependencies Time Series Forecasting

Sep 01 Time Series Forecasting (1): Traditional Statistical Models Time Series Forecasting

Aug 14 PDE and Machine Learning (8): Reaction-Diffusion Systems and Graph Neural Networks PDE and Machine Learning

Jul 30 PDE and Machine Learning (7): Diffusion Models and Score Matching PDE and Machine Learning

Jul 15 PDE and Machine Learning (6): Continuous Normalizing Flows and Neural ODE PDE and Machine Learning

Jun 30 PDE and Machine Learning (5): Symplectic Geometry and Structure-Preserving Networks PDE and Machine Learning

Jun 15 PDE and Machine Learning (4): Variational Inference and the Fokker-Planck Equation PDE and Machine Learning

May 31 PDE and Machine Learning (3): Variational Principles and Optimization PDE and Machine Learning

May 16 PDE and Machine Learning (2) — Neural Operator Theory PDE and Machine Learning

May 01 PDE and Machine Learning (1): Physics-Informed Neural Networks PDE and Machine Learning

Apr 15 Ordinary Differential Equations (18): Frontiers and Series Finale ODE Foundations

Mar 29 Ordinary Differential Equations (17): Physics and Engineering Applications ODE Foundations

Mar 12 Ordinary Differential Equations (16): Fundamentals of Control Theory ODE Foundations

Feb 24 Ordinary Differential Equations (15): Population Dynamics ODE Foundations

Feb 07 Ordinary Differential Equations (14): Epidemic Models and Epidemiology ODE Foundations

Jan 21 Ordinary Differential Equations (13): Introduction to Partial Differential Equations ODE Foundations

Jan 04 Ordinary Differential Equations (12): Boundary Value Problems ODE Foundations

2023

Dec 18 Ordinary Differential Equations (11): Numerical Methods ODE Foundations

Dec 16 HCGR: Hyperbolic Contrastive Graph Representation Learning for Session-based Recommendation Standalone

Dec 01 Ordinary Differential Equations (10): Bifurcation Theory ODE Foundations

Nov 14 ODE Chapter 9: Chaos Theory and the Lorenz System ODE Foundations

Oct 28 ODE Chapter 8: Nonlinear Systems and Phase Portraits ODE Foundations

Oct 15 Kernel Methods: From Theory to Practice (RKHS, Common Kernels, and Hyperparameter Tuning) Standalone

Oct 11 ODE Chapter 7: Stability Theory ODE Foundations

Sep 24 ODE Chapter 6: Linear Systems and the Matrix Exponential ODE Foundations

Sep 20 Position Encoding Brief: From Sinusoidal to RoPE and ALiBi Standalone

Sep 07 ODE Chapter 5: Power Series and Special Functions ODE Foundations

Sep 01 LAMP Stack on Alibaba Cloud ECS: From Fresh Instance to Production-Ready Web Server Standalone

Aug 26 Variational Autoencoder (VAE): From Intuition to Implementation and Troubleshooting Standalone

Aug 22 paper2repo: GitHub Repository Recommendation for Academic Papers Standalone

Aug 21 ODE Chapter 4: The Laplace Transform ODE Foundations

Aug 04 ODE Chapter 3: Higher-Order Linear Theory ODE Foundations

Jul 18 ODE Chapter 2: First-Order Methods ODE Foundations

Jul 13 Session-based Recommendation with Graph Neural Networks (SR-GNN) Standalone

Jul 01 ODE Chapter 1: Origins and Intuition ODE Foundations

Jun 14 Multi-Cloud and Hybrid Architecture Cloud Computing

May 26 Cloud Operations and DevOps Practices Cloud Computing

May 07 Cloud Security and Privacy Protection Cloud Computing

Apr 18 Cloud Network Architecture and SDN Cloud Computing

Mar 30 Cloud Storage Systems and Distributed Architecture Cloud Computing

Mar 13 Learning Rate: From Basics to Large-Scale Training Standalone

Mar 11 Cloud-Native and Container Technologies Cloud Computing

Feb 20 Virtualization Technology Deep Dive Cloud Computing

Feb 01 Cloud Computing Fundamentals and Architecture Cloud Computing

Jan 15 Graph Contextualized Self-Attention Network (GC-SAN) for Session-based Recommendation Standalone

Jan 14 Computer Fundamentals: Deep Dive and System Integration Computer Fundamentals

2022

Dec 27 Lipschitz Continuity, Strong Convexity & Nesterov Acceleration Standalone

Dec 24 Computer Fundamentals: Network, Power, and Troubleshooting Computer Fundamentals

Dec 09 Optimizer Evolution: From Gradient Descent to Adam (and Beyond, 2025) Standalone

Dec 03 Computer Fundamentals: Motherboard, Graphics, and Expansion Computer Fundamentals

Nov 26 LLMGR: Integrating Large Language Models with Graphical Session-Based Recommendation Standalone

Nov 12 Computer Fundamentals: Storage Systems (HDD vs SSD) Computer Fundamentals

Oct 22 Computer Fundamentals: Memory and Cache Systems Computer Fundamentals

Oct 01 Computer Fundamentals: CPU and the Computing Core Computer Fundamentals

Sep 13 LeetCode Patterns: Greedy Algorithms LeetCode Patterns

Aug 29 LeetCode Patterns: Stack and Queue LeetCode Patterns

Aug 14 LeetCode Patterns: Backtracking Algorithms LeetCode Patterns

Aug 05 Multimodal LLMs and Downstream Tasks: A Practitioner's Guide Standalone

Aug 01 Operating System Fundamentals: A Deep Dive Standalone

Jul 30 LeetCode Patterns: Dynamic Programming Basics LeetCode Patterns

Jul 25 Proximal Operator: From Moreau Envelope to ISTA/FISTA and ADMM Standalone

Jul 22 Graph Neural Networks for Learning Equivariant Representations of Neural Networks Standalone

Jul 15 LeetCode Patterns: Binary Tree Traversal and Construction LeetCode Patterns

Jun 30 LeetCode Patterns: Binary Search LeetCode Patterns

Jun 15 LeetCode Patterns: Sliding Window Technique LeetCode Patterns

May 31 LeetCode Patterns: Linked List Operations LeetCode Patterns

May 16 LeetCode Patterns: Two Pointers LeetCode Patterns

May 01 LeetCode Patterns: Hash Tables LeetCode Patterns

Apr 02 Linux Pipelines and File Operations: Composing Tools into Data Flows Linux

Mar 20 Linux Process and Resource Management: From `top` to cgroups Linux

Mar 07 Linux Service Management: systemd, systemctl, and journald Linux

Feb 22 Linux User Management: Users, Groups, sudo, and Security Linux

Feb 09 Linux Package Management: apt, dnf, pacman, and Building from Source Linux

Jan 27 Linux Disk Management: Partitions, Filesystems, LVM, and the Mount Stack Linux

Jan 14 Linux File Permissions: rwx, chmod, chown, and Beyond Linux

Jan 01 Linux Basics: Core Concepts and Essential Commands Linux

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