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Hoc's Playbook

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Here, I organize and summarize study materials related to fundamental topics on the journey to becoming an AI engineer, such as data structures and algorithms, linear algebra, calculus, probability and statistics, cloud computing, and more.

  • Data Structure & Algorithm

    Concepts to Learn:

    • Arrays and Lists
    • Stack anh Queue
    • Linked Lists
    • Trees
    • Heaps
    • Graph
    • Hash
    • Search
    • Sorting
    • Dynamic Programming
    • Greedy
    • Backtracking
    • Divide and Conquer

    👉🏿 Getting started

  • Linear Algebra for AI

    Concepts to Learn:

    • Vector and Matrices
    • Matrix Operations
    • Solving Linear Systems
    • Eigenvalues and Eigenvectors
    • Vector Spaces and Dot Products
    • Optimization.

    👉🏿 Getting started

  • Calculus for AI

    Concepts to Learn:

    • Limits and Continuity
    • Derivatives
    • Integrals
    • Chain Rule
    • Optimization
    • Multivariable Calculus
    • Taylor Series
    • Differential Equations

    👉🏿 Getting started

  • Probability and Statistics for AI

    Concepts to Learn:

    • Probability
    • Random Processes
    • Descriptive and Inferential Statistic
    • Bayesian Statistic
    • Machine Learning Applications
    • Statistical Tests
    • Uncertainty and Noise

    👉🏿 Getting started