πŸ“–
Wiki
CNCFSkywardAIHuggingFaceLinkedInKaggleMedium
  • Home
    • πŸš€About
  • πŸ‘©β€πŸ’»πŸ‘©Freesoftware
    • πŸ‰The GNU Hurd
      • πŸ˜„The files extension
      • πŸ“½οΈTutorial for starting
      • 🚚Continue Working for the Hurd
      • πŸš΄β€β™‚οΈcgo
        • πŸ‘―β€β™€οΈStatically VS Dynamically binding
        • 🧌Different ways in binding
        • πŸ‘¨β€πŸ’»Segfault
      • πŸ›ƒRust FFI
    • πŸ§šπŸ»β€β™‚οΈProgramming
      • πŸ“–Introduction to programming
      • πŸ“–Mutable Value Semantics
      • πŸ“–Linked List
      • πŸ“–Rust
        • πŸ“–Keyword dyn
        • πŸ“–Tonic framework
        • πŸ“–Tokio
        • πŸ“–Rust read files
  • πŸ›€οΈAI techniques
    • πŸ—„οΈframework
      • 🧷pytorch
      • πŸ““Time components
      • πŸ““burn
    • 🍑Adaptation
      • 🎁LoRA
        • ℹ️Matrix Factorization
        • πŸ“€SVD
          • ✝️Distillation of SVD
          • 🦎Eigenvalues of a covariance matrix
            • 🧧Eigenvalues
            • πŸͺCovariance Matrix
        • πŸ›«Checkpoint
      • 🎨PEFT
    • πŸ™‹β€β™‚οΈTraining
      • πŸ›»Training with QLoRA
      • 🦌Deep Speed
    • 🧠Stable Diffusion
      • πŸ€‘Stable Diffusion model
      • πŸ“ΌStable Diffusion v1 vs v2
      • πŸ€Όβ€β™€οΈThe important parameters for stunning AI image
      • ⚾Diffusion in image
      • 🚬Classifier Free Guidance
      • ⚜️Denoising strength
      • πŸ‘·Stable Diffusion workflow
      • πŸ“™LoRA(Stable Diffusion)
      • πŸ—ΊοΈDepth maps
      • πŸ“‹CLIP
      • βš•οΈEmbeddings
      • πŸ• VAE
      • πŸ’₯Conditioning
      • 🍁Diffusion sampling/samplers
      • πŸ₯ Prompt
      • πŸ˜„ControlNet
        • πŸͺ‘Settings Explained
        • 🐳ControlNet with models
    • πŸ¦™Large Language Model
      • ☺️SMID
      • πŸ‘¨β€πŸŒΎARM NEON
      • 🍊Metal
      • 🏁BLAS
      • πŸ‰ggml
      • πŸ’»llama.cpp
      • 🎞️Measuring model quality
      • πŸ₯žType for NNC
      • πŸ₯žToken
      • πŸ€Όβ€β™‚οΈDoc Retrieval && QA with LLMs
      • Hallucination(AI)
    • 🐹diffusers
      • πŸ’ͺDeconstruct the Stable Diffusion pipeline
  • 🎹Implementing
    • πŸ‘¨β€πŸ’»diffusers
      • πŸ“–The Annotated Diffusion Model
  • 🧩Trending
    • πŸ“–Trending
      • πŸ“–Vector database
      • 🍎Programming Languages
        • πŸ“–Go & Rust manage their memories
        • πŸ“–Performance of Rust and Python
        • πŸ“–Rust ownership and borrowing
      • πŸ“–Neural Network
        • 🎹Sliding window/convolutional filter
      • Quantum Machine Learning
  • 🎾Courses Collection
    • πŸ“–Courses Collection
      • πŸ“šAcademic In IT
        • πŸ“Reflective Writing
      • πŸ“–UCB
        • πŸ“–CS 61A
          • πŸ“–Computer Science
          • πŸ“–Scheme
          • πŸ“–Python
          • πŸ“–Data Abstraction
          • πŸ“–Object-Oriented Programming
          • πŸ“–Interpreters
          • πŸ“–Streams
      • 🍎MIT Algorithm Courses
        • 0️MIT 18.01
          • 0️Limits and continuity
          • 1️Derivatives
          • 3️Integrals
        • 1️MIT 6.042J
          • πŸ”’Number Theory
          • πŸ“ŠGraph Theory
            • 🌴Graph and Trees
            • 🌲Shortest Paths and Minimum Spanning Trees
        • 2️MIT 6.006
          • Intro and asymptotic notation
          • Sorting and Trees
            • Sorting
            • Trees
          • Hashing
          • Graphs
          • Shortest Paths
          • Dynamic Programming
          • Advanced
        • 3️MIT 6.046J
          • Divide and conquer
          • Dynamic programming
          • Greedy algorithms
          • Graph algorithms
Powered by GitBook
On this page
  • The techniques related to the N D array
  • Questions

Was this helpful?

Edit on GitHub
  1. πŸ‘©Freesoftware
  2. Algorithm

N D Array

Last updated 1 year ago

Was this helpful?

N D array consists of a sequence of elements. And the elements can be laid out in a rectangular grid rather than a line.

The techniques related to the N D array

  • Simulation technique

  • Diagonal traversal technique

And here are programming techniques related to the N D array:

  • Boundary check

All of these techniques have a basic requirement that the array's edge case must be handled properly. So, you need to know how to handle the edge case of the array. And then do more practice. The N D array part should be ok.

Questions

πŸ‘©β€πŸ’»
🎹
Diagonal Traverse
Spiral Matrix
Pascal's Triangle