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How to use async/await without try/catch block

We can use something like this:

async function resolveToNumber () {
  const promise = Promise.resolve(1)
  const [error, result] = await to(promise)
  console.log(error, result) // [null, 1] -> Here we have the result, and error will be null
}

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Game Mathematics

Linear Algebra

• Vectors

Terminoly

Vector in R²

• Vector: An ordered list of numbers.

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Game Mathematics

Linear Algebra

• Matrices

Writing Systems

$1x + 1y = 5$

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Game Mathematics

Linear Algebra

• Matrices
• • Echelon Forms
• Determinants
• Vectors
• • Vectors
• Eigenvalues

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/*
This JavaScript code snippet implements row reduction algorithms for solving systems of linear equations.
The rowReductionAlgorithms function provides methods for row replacement, interchange, and scaling operations on matrices.
The example cases demonstrate the application of these algorithms to augmented matrices representing systems of linear equations.

The code supports operations like row replacement, interchange, and scaling, providing a flexible tool for solving systems of linear equations.
Each step is illustrated with examples, showcasing the transformation of augmented matrices to their row-reduced echelon form.
*/

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const parseStringPercentToFloat = percentageArray => percentageArray.map(percentage => parseFloat(percentage.slice(0, -1)) / 100);

const parseFloatToStringPercent = percentageArray => percentageArray.map(floatValue => (floatValue * 100).toFixed(2) + "%");

const areArraysEqual = (arr1, arr2) => {
  if (arr1.length !== arr2.length) {
    return false;
  }

  return arr1.every((element, index) => element === arr2[index]);

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//=========================- - Backtracking Algorithms - -=========================//

/*
- Backtracking algorithms:
  are a type of algorithmic technique that is used to solve problems by trying out different
  possible solutions and "backtracking" or undoing a choice when it is found to be incorrect or not feasible.
  These algorithms are useful for solving problems where there are many possible solutions,
  but only a few of them are actually valid or optimal.

- Sudoku puzzles: Backtracking algorithms are often used to solve Sudoku puzzles, which involve filling a 9x9 grid with

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//=========================- - Dynamic Programming Algorithms - -=========================//

/*
- Dynamic Programming:
  is a problem-solving technique that involves breaking down a complex problem into smaller, simpler
  subproblems and solving each subproblem only once, storing the results to avoid redundant calculations.
  The technique is based on the idea of using the solutions of previously solved subproblems to solve the larger problem.

- Optimization problems: Dynamic Programming algorithms can be used to solve optimization problems, such as the Knapsack
  problem, where the goal is to maximize the value of objects that can be placed in a knapsack subject to its weight capacity.

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//=========================- - Search Algorithms - -=========================//

//- Binary Search

//Binary Search assumes that the input array is already sorted in ascending order.
function binarySearch(arr: number[], target: number, start = 0, end = arr.length - 1) {
  if (start > end) return -1

  const mid = Math.floor((start + end) / 2)

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// - - Sorting Algorithms
// - Bubble Sort - O(n^2) - Quadratic Time
// - Merge Sort - O(n log n) - Quasilinear Time
// - Quick Sort - O(n log n) - Quasilinear Time
// - Heap Sort - O(n log n) - Quasilinear Time
// - Counting Sort - O(n + k) - where k is the range of the input integers
// - Radix Sort - O(d(n+k)) - where d is the number of digits in the input integers and k is the range of the input integers
// - Bucket Sort - O(n + k) - where k is the number of buckets used
// - insertion sort - O(n^2) - Quadratic Time
// - selection sort - O(n^2) - Quadratic Time