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📚 Tech Notes

This KB is a collection of notes, implementations, and concepts I've gathered over time.

It's a mix of Data Structures and Algorithms (DSA), System Design, Machine Learning concepts, and more.

It's a structured dump of stuff I've pulled out of old word files and tweaked into linkable artifacts

Table of Contents​

Design Systems​

This section focuses on building specific systems, often inspired by technical interviews or real-world use cases. Examples include URL shorteners, YouTube Search, Top K Heavy Hitters, and more.

To implement these systems, you'll find notes on Databases, Messaging, Calculations, and other essential components.

Databases and Storage​

  • Covers SQL and NoSQL architectures/products.
  • Includes discussions on Relational Databases, NoSQL Key-Value Stores, Blob Storage, and Data Warehousing Solutions.

Messaging​

  • Explains how to send messages between services using Queues, Brokers, and Pub/Sub systems.

Typical Resources​

  • Discussions and implementations of "typical" resources like:
    • Distributed Key-Value Stores.
    • Front-end Load Balancers with Metadata.
    • Distributed Queues.
  • Includes Kubernetes (K8s) and Terraform configurations to demonstrate how to create these systems natively.

DSA​

This section contains:

  • General Data Structures and Algorithms.
  • Their implementations, time/space complexities, and use cases.

Other Concepts​

This section includes generic concepts that don't fit into DSA or System Design, such as:

  • Embeddings.
  • Parallel Training Designs.
  • Pregel Graph Traversals.

These are useful but don't belong in the other categories.

Implementations​

A collection of generic implementations, including:

  • A Key-Value Store with Transactions.
  • A Balanced Binary Search Tree from Scratch.
  • ML Feature Store Architecture Diagram.

Leet​

This is a dump of Leetcode problems and comments, organized for easy reference.

Arxiv​

These are just papers I've read marked up with highlighter - my old iPad died and brought these here

References​

These are some of the resources I frequently use and reference throughout this repo:

Why This?​

This repo is meant to be a reference hub for anyone interested in:

  • Learning DSA and System Design.
  • Exploring Machine Learning concepts like embeddings and attention mechanisms.
  • Understanding real-world system implementations.

Feel free to explore, contribute, or use it as a learning resource!