Under the Hood

Machine Learning

In this section, I have covered the basics of how these learning systems work, like understanding "neural networks" (which are inspired by the human brain!) and how they process information.

• Neural Networks 101: Understanding the Basics
• Neural Networks 101: Forward Propagation
• Activation Functions in Neural Networks
• Stochastic Gradient Descent: A Basic Explanation
• Understanding Backpropagation: The Engine Behind Neural Networks
• A Gentle Introduction to Optimizing Gradient Descent
• Exploring Loss Functions in Machine Learning
• ArgMax and SoftMax
• Shallow Neural Networks
• Regularization: The Key to Building Better Machine Learning Models
• Overfitting Has Many Faces
• Why Hyperparameters Matter!
• Curse of Dimensionality
• The Art of Feature Engineering
• Correlation in Machine Learning: What You Need to Know
• Ensemble Learning: A Beginner's Guide
• Unveiling Multivariate Shallow Neural Network Magic
• The Power of Recurrent Neural Networks: A Fun Introduction
• Pooling: A Key Concept in Machine Learning
• ImageNet Classification with Deep Convolutional Neural Networks
• Adaptive Learning with Machine Learning
• Backpropagation of Simple Expression
• Gradient Descent: Applications in Machine Learning
• The Curse of Local Minima: How to Escape and Find the Global Minimum

Database Systems

Here You'll learn how databases make sure that the information is accurate and doesn't get lost, even if the computer crashes!

• Ted Codd's Legacy: From Flat Files to Relational Power
• Let's Dig Into the Life Cycle of a Transaction In Database
• Atomic Transactions: The Bedrock of Reliable Database Systems
• Atomicity: The All-or-Nothing Guarantee That Protects Your Data
• System Crash? No Sweat! The UNDO Log to the Rescue
• WAL on a Roll: How Databases Handle Large Transactions and Rollbacks
• When the Log is Full: How Databases Prevent Data Loss During WAL/REDO Log Overflow
• DBMS Behavior: How Different Systems Handle the Void
• Django's Database Connection Management Architecture
• The Dual Nature of Data Access: Sequential vs. Random in Database Systems
• Why mmap is a Bad Idea for Databases?
• Building a Database From Scratch: Why mmap Falls Short

C Programming and Memory Management

We'll explore different ways to store information in memory and how to make sure your programs use memory efficiently.

• Stacking the Odds in Your Favor: Unpacking the Speed of the Execution Stack
• Hidden Costs of Freedom: Understanding Heap Performance
• Understanding Bit Manipulation in C
• How to Access a Single Bit: Understanding Bit Manipulation in C
• Finding the Right Byte: A Guide to Addressing, Memory, and Data Organization
• Understanding Address Calculation in Memory Management
• Dynamic Memory Allocation and Address Calculation
• Allocating Memory Until Failure
• The Cost of Convenience: Implications of Padding in Network Programming
• Using Pragma Directives to Control Struct Padding
• Why C Still Holds My Heart: My Confession
• Implementing a Custom Buffer Management System

Computer Architecture and Hardware

Here You'll learn how the CPU (the brain of your computer), memory, and storage all work together to make your computer run.

• Dance of the Data
• The Power of Predictability: How Sequential Access Unlocks Hardware Performance
• From HDDs to Caches: How Sequential Access Optimizes Data Flow
• From Files to Databases: Understanding the Impact of Sequential and Random Access
• Record-Based Paginated Access
• The Hidden World of Cache: Understanding its Impact on Random Access Performance
• Bringing Cache to Life: Simulating a Two-Level Cache System in C
• Load, Store, and Optimize: How Caches Bridge the Gap Between CPU Speed and Memory Latency
• Why Stack is So Fast?
• Have you ever wondered how DRAM, the common memory in our computers, actually works?
• Inside the Memory Controller: Unlocking the Power of Address Translation and Command Scheduling
• How CPUs Talk to DRAM: Exploring the Memory Access Pipeline
• Deep Dive into Memory Controllers: Mastering Read/Write Grouping for Optimal Performance
• Implementing Cache Management in Memory Controllers
• Everything You Need to Know About Prefetching
• Hardware Prefetching
• Boosting Program Speed with Software Prefetching
• Hybrid Prefetching: Memory Performance with Hardware and Software

Advanced Machine Learning

Once you understand the basics of Machine Learning, this section takes you to the cutting edge! You'll learn about powerful new techniques and systems that are pushing the boundaries of what computers can learn.

• Machine Learning Operations: Overview, Definition, and Architecture
• Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
• Language Models Prompting Elicits Reasoning in Large Language Models
• Locating and Editing Factual Associations in GP

Operating Systems

Here You'll learn how the "operating system" acts like the boss, managing all the different parts of your computer and making sure everything runs smoothly.

• From Bits to Bytes: Understanding Sequential Access in Memory and Storage
• One Core, Many Threads: The Art of Single-CPU Multithreading
• Why You Shouldn't Read Directly from Disk
• Beyond the CPU: Exploring the Memory Controller's Role in Computing
• Beyond Single-Core: Orchestrating Threads Across Cores
• Optimizing Memory Access: A Practical Guide to Scheduling Algorithms
• Multithreading in a Single CPU
• Multithreading on Multiple CPUs
• Linux's Cloning Trick: Understanding fork() and the Magic of Copy-on-Write
• The Magic of Page Tables
• Inside the Page Table: A Deep Dive into Virtual Memory Mapping
• When Virtual Memory Hits a Bottleneck?
• Beyond RAM: The Hidden World of Page Tables, Large Pages, and Efficient Memory
• Why Your Computer Isn't as Slow as You Think: The Magic of the TLB
• From Virtual to Physical: A Step-by-Step Guide to Page Table Operations
• Concurrency and Memory Models: Why Your Multi-Threaded Code Might Not Behave As Expected
• Out of Memory Killer
• Ever Wonder How Linux Survives When it Runs Out of Memory?

Parallel Computing and CUDA

You'll learn how to use powerful graphics cards (GPUs) to speed up your programs. We'll use CUDA, a special language that helps you write programs for GPUs.

• Introduction to CUDA
• CUDA Beyond the Basics
• Unlocking CUDA's Potential: Thread Hierarchy and Parallel Execution

Software Architecture

This section is about designing and building strong, well-organized software systems.

• Deep Dive into Monolith and Microservices
• Event-Driven Architectures

Frontend Development

We'll cover important web technologies and learn how to use frameworks that make building websites easier.

• Everything About HTTP
• Domain Name System
• Introduction to TypeScript
• Introduction to Angular
• Modules and Routers
• Components, Metadata and Data Binding
• Getting into Component of Angular

DevOps

This section is about building and delivering software faster and more reliably.

• Docker
• Kubernetes
• Kafka
• Quarkus

Distributed Systems

This section teaches you how to design and build these complex systems.

• The Clockwork of Distributed Systems: A Guide to Timestamping Solutions (Part-1)
• The CAP Theorem: Often Misunderstood