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#problem_solving_002 Find the Sum All Primes for example;- sumPrimes(10) should return a number, 17. or sumPrimes(977) should return 73156. NB: 1. You can use Any Language you can 2. you can send you answer at @fightAgainNow or comment below

👏🏼👏🏼Solved!📌✅✅✅ @bbbburp - used python @Nathanzgreat -used python @wub1624 - used C++ @Faris273 - used python @KevinDeAaron - used python thanks for your 🥰 participation.

#Problem_Solving_001 Find the Sum OF All Numbers in given a Range. or example, sumOfAll([10,5]) should return 45 because sum of all the numbers between 5 and 10 (both inclusive) is 45. NB: 1. You can use Any Language you can 2. send you answer only at @fightAgainNow

Top 8 Algorithms Every Programmer Should Know 💯 1.Sorting algorithms: Sorting is a fundamental operation in computer science and there are several efficient algorithms for it, such as quicksort, merge sort and heap sort. 2.Search algorithms: Searching for an element in a large dataset is a common task and there are several efficient algorithms for it, such as binary search and hash tables. 3.Graph algorithms: Graph algorithms are used to solve problems related to graphs, such as finding the shortest path between two nodes or determining if a graph is connected. 4.Dynamic programming: Dynamic programming is a technique for solving problems by breaking them down into smaller subproblems and storing the solutions to these subproblems to avoid redundant computation. 5.Greedy algorithms: Greedy algorithms are used to solve optimization problems by making the locally optimal choice at each step with the hope of finding a global optimum. 6.Divide and Conquer: Divide and Conquer is an algorithm design paradigm based on multi-branched recursion. A divide and conquer algorithm breaks down a problem into sub-problems of the same or related type, until these become simple enough to be solved directly. 7.Backtracking: Backtracking is a general algorithmic technique that considers searching every possible combination in a systematic manner, and abandons a particular path as soon as it determines that it cannot be part of the solution. 8.Randomized Algorithm: Randomized algorithms use randomness to solve a problem. It can be useful to solve problems that cannot be solved deterministically or to improve the average case complexity of a problem.

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