1593347004

The Greedy Method is an approach for solving certain types of optimization problems. The greedy algorithm chooses the optimum result at each stage. While this works the majority of the times, there are numerous examples where the greedy approach is not the correct approach. For example, let’s say that you’re taking the greedy algorithm approach to earning money at a certain point in your life. You graduate high school and have two options:

#computer-science #algorithms #developer #programming #greedy-algorithms #algorithms

1593347004

The Greedy Method is an approach for solving certain types of optimization problems. The greedy algorithm chooses the optimum result at each stage. While this works the majority of the times, there are numerous examples where the greedy approach is not the correct approach. For example, let’s say that you’re taking the greedy algorithm approach to earning money at a certain point in your life. You graduate high school and have two options:

#computer-science #algorithms #developer #programming #greedy-algorithms #algorithms

1626421931

In this post, we will look at the solution for **Coin Change Problem** using **Greedy Algorithm**.

But before that, let’s understand what Greedy Algorithms are in the first place.

**Greedy Algorithms** are basically a group of algorithms to solve certain types of problems. The key part about greedy algorithms is that they try to solve the problem by **always making a choice that looks best for the moment** .

The famous **coin change problem** is a classic example of using greedy algorithms.

Below is an implementation of the above algorithm using C++. However, you can use any programming language of your choice.

While the coin change problem can be solved using the Greedy algorithm, there are scenarios in which it does not produce an optimal result.

#tutorial #algorithm #data structure #algorithm analysis #greedy algorithm

1585908703

What is Greedy Method

Before discussing the Fractional Knapsack, we talk a bit about the Greedy Algorithm. Here is our main question is when we can solve a problem with Greedy Method? Each problem has some common characteristic, as like the greedy method has too. Such as if a problem contains those following characteristic , then we can solve this problem using greedy algorithm. Such as

- Maximization or minimization . not twins together
- Problem solution
- Constraints
- Requirements
- Feasible solution
- See elements in each stages
- And finally optimal solution

Look at the name of the method, Greedy Method. That is, we have to solve our problem in a straightforward way so that we can profit. That is, how much we can maximize or minimize when needed.The problem that is given is that there must be a solution.Because without solution, there can be no problem. This problem will have some constraints or limitations. That means we will be given a range beyond which we cannot work.

#algorithm #greedy #greedy method #knapsack #fractional

1593350760

Learn what are metaheuristics and why we use them sometimes instead of traditional optimization algorithms. Learn the metaheuristic Genetic Algorithm (GA) and how it works through a simple step by step guide.

#genetic-algorithm #algorithms #optimization #metaheuristics #data-science #algorithms

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**Objectives of this article:**

- Describe what is the importance of a Data Structure
- Describe the term Algorithm
- What are algorithm complexities
- Approaches to solving algorithms

This particular concept is identified as one of the most important concepts in software engineering, and that became a primary checkpoint for most of the top-level companies. In this lesson series, we will discuss the idea behind data structures and algorithm concepts, and we will implement several algorithms during upcoming lessons.

The simple definition for the data structure is that “**different ways of storing data on your computer**” or “the systematic way of representing and organizing your data”. Importantly, any data structure should be able to use efficiently for any given task. for instance, search, transform data, edit, update, etc.

There are three different features of a data structure that we can categorize based on the usage.

**Time complexity**

*Running time or the execution time for a given task is defined as the time complexity. We should use the best possible data structure for the given context to minimize the time complexity as much as possible.*

**Correctness based on the particular interface**

_Every data structure comprises its _**_interface _***that the operations that support by the given data structure. Similarly, there should be a correct implementation of the data structure based on the correct interface. Ideally, a data structure should come with a correctly defined interface and descriptive implementation.*

**Space Complexity**

*Space complexity will measure the memory usage of a given data structure. Ultimately, we should optimize our algorithmic solution to minimize space complexity as much as possible for solutions with a large number of data sets.*

Nowadays, with the development of new processors, computer systems, handling a large number of data records with our normal computers is not a complex or exhaustive task. But, when it comes to certain unpredictive conditions based on a few criteria like **data size**, **retrieval speed**, and **multi-thread processing** we should focus on implementing a proper data structure for the given scenario.

Imagine that you are implementing a simple text search based on a big text corpus with more than millions of records. If you are trying to process data objects parallelly and if your execution time should not exceed sub milliseconds.

The properly designed data structure will help you to achieve those types of tasks in an efficient manner.

An algorithm is a step-by-step procedure to achieve any task. In other words, an algorithm is a well-defined set of unambiguous instructions to achieve a given task without relies on any particular programming language. In this series, we will try to implement major data structures and algorithms in nodejs and python programming languages to see the similarity of any given algorithm.

#data-structure-algorithm #divide-and-conquer #algorithms #greedy-algorithms #data science