#memoization

[filestack]

Memoization | Filestack

Memoization is a performance optimization technique used to accelerate applications. It involves storing the results of resource-intensive function calls. This way, if the same inputs are used in the future, the function can return the cached result, avoiding the need to recomputed it. If you want to explore more about Memoization, take a look at this blog.

[codewithnazam]

React Conditional Rendering

#react #conditionalrendering

React is a popular JavaScript library that allows developers to build interactive user interfaces (UI) for web applications. One of the key features of React is its ability to perform conditional rendering, which means that the rendering of a component or element depends on certain conditions being met. In this article, we will explore the concept of conditional rendering in React, its benefits,…

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[codesolutionsstuff]

What is memoization?

A programming technique called memory seeks to improve function performance by caching previously computed results. The parameters of a memoized function are used each time it is invoked to index the cache. Without running the complete code, the data can be returned if it is present. If not, the function is called, and the output is then cached. Dynamic programming uses a particular kind of caching called memorization. By using caching, we can speed up our programs and store some data in an easily accessible location for future use. When we call immediately, it returns the others immediately while storing the prior result. Additionally, when the same set of arguments yields the same output and performant online applications, memoization is a cache optimization approach.

Fibonacci sequence

Without having to memorization it, let's develop a function that computes the Fibonacci sequence. Each value in the Fibonacci sequence is a list of numbers where the sum of the two values before it. // fibonacci without memoization const fib = (num) => { if (num < 2) { return 1 } else if (!num || typeof num !== 'number') { return 'value must be a number!' } return fib(num - 1) + fib(num - 2) } console.log(fib(10)) As you can see from the code above, we didn't cache how our function was used. With caching, the process will go much more quickly and in less time. // fibonacci sequence with memoization to run the function fib() const fib = (num) => { let cache = {}; // set cache // if exists in cache return from cache if (cache !== undefined) { console.log(`${num} is cached!`); return cache; } // if not in cache perform operation cache = num < 2 ? 1 : fib(num - 1) + fib(num - 2); return cache; } const result = fib(5) console.log(result) // 8 We produced a cache object from the aforementioned code piece, which the fib() utilises to store its output value. Every time the function is called, the first thing it does is see if the input num has already been saved in the cache object. If so, the application immediately returns the stored value.

Exercise

Let's use the factorial() function's cache execution to get the factorial of a given number. // factorial of a number with memoization (cache execution) const factorial = (num) => { let cache = {}; // set cache // if cache already exists, return cache if (cache !== undefined) { console.log(`${num} is cached!`); return cache; // edge case validation for not a number } else if(!num || typeof num != 'number') { return `value must be a number` } cache = num === 0 ? 1 : num === 2 ? 2 : num * factorial(num - 1); // condition ternary operator, same with if/else statement return cache; }; console.log(factorial(5)); // 120 Read the full article

[codesolutionstuff]

What is memoization?

New Post has been published on https://www.codesolutionstuff.com/what-is-memoization/

What is memoization?

A programming technique called memory seeks to improve function performance by caching previously computed results. The parameters of a memoized function are used each time it is invoked to index the cache. Without running the complete code, the data can be returned if it is present. If not, the

[winstonmhangoblog]

Python fibonacci sequence and memoization. One of the more daring data handling procecces in programming is when recursion and automation data generations are involved. Fibonacci sequence is one of the ways data can be generated using certain mathematical patterns. But if it gets slow and big,some mechanism to optimize data loading for such algorithms need to be employed.And that's where memoization come in. In this slide set,I show you just Abit of what fibonacci sequence are and how to use memoization to solve the slow data loads . #python #fibonaccisequence #memoization #datageneration #computerscience #algorithms #datastructures (at Lilongwe, Malawi) https://www.instagram.com/p/CKWoyOCgxEA/?igshid=1gnb4vn71rhoz

[mother-sauces]

Day 29: Unique Paths

Time to finish the month strong!

A robot is located at the upper-left corner of an m x n grid. The robot can only take one step at a time, moving either down or right. How many unique paths are there that take the robot to the bottom-right corner?

If you haven't seen it before, this is a pretty classic problem for learning Dynamic Programming. We can describe it as an elegant induction problem, and use that to write an elegant program.

Consider: for most grids, the robot has to move either right or down. If it moves right, it's now at the upper-left corner of an (m-1) x n grid. For moves downward, we reduce n by 1. Add those together, and you have a solution. For an easy base case, a 1 x 1 grid has 1 unique path.

If you code this naively, it might be too slow on its own. You can improve the base cases or exploit the symmetry, but I really like memoization: caching previously calculated results. You'll often be able to reuse solutions to subproblems, almost as if you're a hoity-toity functional programmer.

9 LOC

[myfreecourses]

Recursion and Backtracking (Memoization, D&C, Combinations)

Recursion and Backtracking (Memoization, D&C, Combinations)

Algorithm Design Techniques, Backtracking, Divide and Conquer, Memoization, N-queen Problem What you’ll learn

You will be able to solve almost any problem involving recursion or at least easily understand the logic behind it.

You will learn Backtracking and be able to solve famous Backtracking problems that may be asked in the coding interviews.

You will have the sufficient knowledge and…

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[syndicode]

Exploring Ruby memoization and the alternatives

“I always knew that one day smalltalk would replace Java. I just didn’t know it would be called Ruby.” Now we know! There are so many things to tell about Ruby that nobody can stop us. Today let’s go into exploring Ruby memoization and the alternatives with us. It’s co...