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Posts that continue over several parts, grouped by series. Read from the top to follow a topic from start to finish.

Computer Networking 20 parts

  1. [Computer Networking] 01. What Is the Internet?
  2. [Computer Networking] 02. Network Core: Packet Switching vs Circuit Switching
  3. [Computer Networking] 03. Network Delay, Loss, and Throughput
  4. [Computer Networking] 04. Protocol Layers and Service Models
  5. [Computer Networking] 05. Application Layer: HTTP and the Web
  6. [Computer Networking] 06. DNS and Email Protocols
  7. [Computer Networking] 07. Socket Programming: TCP and UDP
  8. [Computer Networking] 08. Transport Layer: Multiplexing/Demultiplexing and UDP
  9. [Computer Networking] 09. Principles of Reliable Data Transfer
  10. [Computer Networking] 10. TCP Deep Dive: Connection, Flow Control, Congestion Control
  11. [Computer Networking] 11. Network Layer Overview: Forwarding and Routing
  12. [Computer Networking] 12. IP Protocol: Datagrams and Addressing
  13. [Computer Networking] 13. Routing Algorithms: Link-State and Distance-Vector
  14. [Computer Networking] 14. Internet Routing: OSPF and BGP
  15. [Computer Networking] 15. Link Layer: Error Detection and Multiple Access Protocols
  16. [Computer Networking] 16. Ethernet, Switches, and VLANs
  17. [Computer Networking] 17. Wireless Networks and Mobile Communications
  18. [Computer Networking] 18. Multimedia Networking and Streaming
  19. [Computer Networking] 19. Network Security: From Cryptography to Firewalls
  20. [Computer Networking] 20. Network Management and SNMP

Compiler 20 parts

  1. [Compiler] 01. Compiler Structure and How It Works
  2. [Compiler] 02. Programming Language Basics and Compiler Technology Applications
  3. [Compiler] 03. Building a Simple Syntax-Directed Translator
  4. [Compiler] 04. Lexical Analysis - Tokens, Patterns, and Regular Expressions
  5. [Compiler] 05. Finite Automata and Lexical Analyzer Implementation
  6. [Compiler] 06. Syntax Analysis (1) - Top-Down Parsing and LL Parsers
  7. [Compiler] 07. Syntax Analysis (2) - Bottom-Up Parsing and LR Parsers
  8. [Compiler] 08. Syntax-Directed Translation - SDD and SDT
  9. [Compiler] 09. Intermediate Code Generation - Three-Address Code and Type Checking
  10. [Compiler] 10. Runtime Environments - Stack, Heap, and Garbage Collection
  11. [Compiler] 11. Code Generation - Basic Blocks and Flow Graphs
  12. [Compiler] 12. Code Generation Algorithms and Register Allocation
  13. [Compiler] 13. Machine-Independent Code Optimization Basics
  14. [Compiler] 14. Data-Flow Analysis Framework
  15. [Compiler] 15. Loop Optimization and Code Motion
  16. [Compiler] 16. Instruction-Level Parallelism and Scheduling
  17. [Compiler] 17. Parallelism Detection and Loop Transformations
  18. [Compiler] 18. Interprocedural Analysis and Pointer Analysis
  19. [Compiler] 19. SSA Form and Modern Compiler Optimization
  20. [Compiler] 20. Modern Compiler Development and Applications

OS Concepts 20 parts

  1. [OS Concepts] 01. What is an Operating System
  2. [OS Concepts] 02. Operating System Structures and Services
  3. [OS Concepts] 03. Processes: Concepts, Creation, Communication
  4. [OS Concepts] 04. Threads and Concurrent Programming
  5. [OS Concepts] 05. CPU Scheduling Algorithms
  6. [OS Concepts] 06. Process Synchronization Tools
  7. [OS Concepts] 07. Synchronization Problems: Producer-Consumer, Dining Philosophers
  8. [OS Concepts] 08. Deadlocks: Prevention, Avoidance, Detection, Recovery
  9. [OS Concepts] 09. Main Memory Management
  10. [OS Concepts] 10. Virtual Memory: From Demand Paging to Thrashing
  11. [OS Concepts] 11. Mass-Storage Structure
  12. [OS Concepts] 12. I/O Systems
  13. [OS Concepts] 13. File-System Interface
  14. [OS Concepts] 14. File-System Implementation
  15. [OS Concepts] 15. File-System Internals
  16. [OS Concepts] 16. Security: Threats and Defenses
  17. [OS Concepts] 17. Protection: Access Control and Sandboxing
  18. [OS Concepts] 18. Virtual Machines: From Hypervisors to Containers
  19. [OS Concepts] 19. Networks and Distributed Systems
  20. [OS Concepts] 20. Linux and Windows 10 Operating System Comparison

Deep RL 20 parts

  1. [Deep RL] 01. What is Reinforcement Learning: MDP and Fundamental Concepts
  2. [Deep RL] 02. Getting Started with Reinforcement Learning Using OpenAI Gym
  3. [Deep RL] 03. PyTorch Deep Learning Basics: From Tensors to Neural Networks
  4. [Deep RL] 04. Solving CartPole with the Cross-Entropy Method
  5. [Deep RL] 05. Bellman Equation and Value Iteration
  6. [Deep RL] 06. Deep Q-Network: Principles and Implementation of DQN
  7. [Deep RL] 07. DQN Extensions: Double DQN, Dueling DQN, Rainbow
  8. [Deep RL] 08. Building a Stock Trading Agent with Reinforcement Learning
  9. [Deep RL] 09. Policy Gradient: Policy-Based Reinforcement Learning
  10. [Deep RL] 10. Actor-Critic Methods: A2C and Hyperparameter Tuning
  11. [Deep RL] 11. A3C: Asynchronous Advantage Actor-Critic
  12. [Deep RL] 12. Training Chatbots with Reinforcement Learning
  13. [Deep RL] 13. Web Navigation and Reinforcement Learning
  14. [Deep RL] 14. Continuous Action Spaces: DDPG and Distributional Policies
  15. [Deep RL] 15. Trust Region Methods: TRPO, PPO, ACKTR
  16. [Deep RL] 16. Black-Box Optimization: Evolution Strategies and Genetic Algorithms
  17. [Deep RL] 17. Model-Based Reinforcement Learning: Imagination-Augmented Agent
  18. [Deep RL] 18. AlphaGo Zero: AI That Learns by Playing Itself
  19. [Deep RL] 19. Practical Applications of Deep Reinforcement Learning
  20. [Deep RL] 20. Deep RL Summary: Algorithm Comparison and Selection Guide

Virtualization 10 parts

  1. [Virtualization] 01. Virtualization Fundamentals: Type 1 vs Type 2 Hypervisors
  2. [Virtualization] 02. QEMU and KVM: The Heart of Open-Source Virtualization
  3. [Virtualization] 03. VirtualBox and VMware: From Desktop to Enterprise
  4. [Virtualization] 04. Complete Guide to GPU Virtualization: Passthrough, vGPU, MIG, SR-IOV
  5. [Virtualization] 05. AWS EC2 and Nitro System: The Evolution of Cloud Virtualization
  6. [Virtualization] 06. KubeVirt: Running VMs on Kubernetes
  7. [Virtualization] 07. NVIDIA GPU Operator: Automating GPU Management on Kubernetes
  8. [Virtualization] 08. KubeVirt + GPU: Leveraging GPU Acceleration in VMs
  9. [Virtualization] 09. Virtualization Platform Comparison: QEMU vs VirtualBox vs VMware vs KubeVirt
  10. [Virtualization] 10. The Future of Virtualization: From Confidential Computing to GPU Disaggregation

AI Era Survival Guide 8 parts

  1. AI Era Survival Guide Part 1: From Developer to DevOps/Platform Engineer — Roadmap and Realistic Strategy
  2. AI Era Survival Guide Part 2: Transitioning from Developer to LLM Engineer / AI Engineer
  3. AI Era Survival Guide Part 3: A Complete Guide to AI Tools for Accountants and Lawyers
  4. AI Era Survival Guide Part 4: AI Literacy and Survival Strategies for Every Professional
  5. AI Era Survival Guide Part 5: The Future of Data Scientists - Crisis or Opportunity?
  6. AI Era Survival Guide Part 6: How Planners and PMs Can Evolve into AI Product Managers
  7. AI Era Survival Guide Part 7: A Special Guide for Junior Developers - Growing Alongside AI
  8. AI Era Survival Guide Part 8: Survival Strategies for Designers in the Age of Midjourney and Figma AI

Inside vLLM 7 parts

  1. Inside vLLM (1) — The Full Path From One Request to One Token
  2. Inside vLLM (2) — Why PagedAttention Splits the KV Cache Into Pages
  3. Inside vLLM (3) — How Continuous Batching Keeps the GPU Busy
  4. Inside vLLM (4) — The Scheduler and Preemption, Where Throughput Collapses
  5. Inside vLLM (5) — Prefix Caching, and Why System Prompt Design Is Performance
  6. Inside vLLM (6) — Context Window vs max_model_len vs max_tokens, Fully Explained
  7. Inside vLLM (7) — Deployment Tuning, Common Pitfalls, and OOM Triage

Open Source Worth Watching Right Now 6 parts

  1. Open Source Worth Watching Right Now (1) AI Agents and LLM Tooling
  2. Open Source Worth Watching Right Now (2) Build Tools, Editors, CLIs, and Terminals
  3. Open Source Worth Watching Right Now (3) Infrastructure and Databases
  4. Open Source Worth Watching Right Now (4) Observability and Security
  5. Open Source Worth Watching Right Now (5) Data and ML Pipelines
  6. Open Source Worth Watching Right Now (6) What Star Counts Do Not Tell You

tiny-models 5 parts

  1. AI for Everyone, Part 1 — Training a 16M-Parameter Language Model From Scratch in 15 Minutes
  2. AI for Everyone, Part 3 — Loss of 0.0017, Accuracy of 7.5%: The Culprit Was One Padding Slot
  3. AI for Everyone, Part 4 — Captioning Images With 1.37M Parameters, and Why Part 3 Bug Was Absent Here
  4. AI for Everyone, Part 5 — Colourising Photos With a 0.47M U-Net, and Why the Colours Came Out Washed Out
  5. AI for Everyone, Part 6 — Drawing Digits From Words With a 1.11M Diffusion Model

part 4 parts

  1. ch01 LangChain Notes
  2. ch02 LangChain Notes
  3. ch03 LangChain Notes
  4. ch04 LangChain Notes

ch 2 parts

  1. Building an AWS Pipeline Ch 01
  2. Building an AWS Pipeline Ch 02