Jason's Notebook

Knowledge Vault

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books
10
total notes
522
last edited
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Overview

Welcome to the Knowledge Vault—a structured personal knowledge base and digital garden tracking the core domains of computer science, hardware systems, artificial intelligence, software engineering, mathematics, physics, and robotics. This repository connects foundational theoretical principles with practical engineering implementations, systems architecture, and problem-solving patterns.

Primary Knowledge Books

1. Computer Science & Theory

  • Computer Science Introduction
    Classical algorithm design (Divide & Conquer, Dynamic Programming, Greedy), core Abstract Data Types, C/C++ language mechanics (templates, STL), and software engineering principles.
  • Computer Science Theory
    Formal mathematical foundations including discrete structures, combinatorics, graph theory, recurrences, automata, formal languages, and computability theory.
  • LeetCode
    Algorithmic problem-solving patterns, data structure manipulations, runtime optimizations, and technical interview preparation.

2. Systems & Infrastructure

  • Computer Systems
    The full hardware-software stack—spanning Digital Systems (boolean logic, ALUs, FSMs), Computer Architecture, Operating System Kernels (scheduling, memory, file systems), and low-level System Programming in C.
  • Development Environment
    Developer tooling, terminal workflows, shell scripting, Git version control, and debugging environments.

3. Artificial Intelligence & Data Science

  • Artificial Intelligence
    Intelligent agent architectures, search algorithms, classical machine learning models, deep learning networks (CNNs, Transformers, GANs), reinforcement learning, and ethical AI policy frameworks.
  • Machine Learning Systems
    System-level software architectures, model training infrastructure, edge deployment, and MLOps.
  • Data Science
    Descriptive analytics, statistical inference, data visualization, model evaluation metrics, sampling methodologies, and domain-specific ML applications.

4. Mathematical & Physical Sciences

  • Mathematics
    Mathematical foundations across Algebra, Calculus, Trigonometry, and Applied Statistics.
  • Physics
    Fundamental physical laws and systems encompassing Classical Mechanics, Thermodynamics, Electricity & Magnetism, Optics, and Early Quantum Physics.
  • Robotics
    Kinematics, dynamics, motion planning, spatial reasoning, control systems, and computer vision integration for physical autonomous systems.

About This Documentation

This is my digital workspace where I organize and maintain notes from various subjects I’m studying. The content is structured to help me quickly find and review concepts, solutions, and insights I’ve gathered over time.

Feel free to browse through the different sections using the navigation or search functionality.

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