ML&COMPUTERSCIENCEARCHIVE
Curated collection of high-impact learning sources, Machine Learning deep dives, WebGL shader breakdowns, and system engineering papers.
Machine Learning Fundamentals & Core Concepts
In-depth guide explaining fundamental Machine Learning principles, models, and real-world execution strategy.
Visualizing Neural Networks & Backpropagation
Mathematical intuition and 3D geometric visualization of deep neural network weights, biases, and gradient descent.
Understanding Transformer Models & Self-Attention
The seminal research paper introducing the Transformer architecture, multi-head attention mechanisms, and sequence encoding.
Creative WebGL & GLSL Custom Shader Mastery
Live breakdown of advanced WebGL shader programming, raymarching, and interactive GPU noise fields.
Designing High-Availability Microservices & Data Pipelines
Comprehensive pattern collection for event-driven architecture, CQRS, saga pattern, and fault tolerance.
Server Components, Streaming & Cache Invalidation
Deep dive into React Server Components (RSC), hydration boundaries, route handlers, and streaming SSR.
How to Add New Learning Sources
All learning items are stored in app/learn/data/learning-sources.json. No database required. You can add YouTube embeds, articles, or courses simply by appending a new JSON object to the array file.
// Edit: app/learn/data/learning-sources.json
[
{
"id": "ml-ai-with-thakshila",
"name": "ML",
"title": "Machine Learning Foundations & Algorithms",
"url": "https://youtu.be/WAhLGfQ9LG8?si=8XNtQ_VOvAAviCLJ",
"embedUrl": "https://www.youtube.com/embed/WAhLGfQ9LG8",
"source": "Youtube",
"credits": "Ai with Thakshila",
"category": "Machine Learning",
"type": "video",
"description": "Comprehensive tutorial explaining core ML concepts...",
"tags": ["Machine Learning", "AI", "Algorithms"]
}
]