DefinitionAn algorithm is a collection of instructions for performing a specific computation or operation. Algorithms originated in mathematics – the word “algorithm.” It comes from the Arabic writer Muhammad ibn Ms al-Khwrizm. An algorithm is a simple, unambiguous definition of what needs to be done. An algorithm generates a specific set of results. It could return the greater of the two numbers, an all-uppercase version of a phrase, or a sorted list of numbers. An algorithm is guaranteed to finish and generate a result after a finite amount of time. If an algorithm could run indefinitely, it would be useless because you would never get a response. The accuracy of the majority of algorithms is assured. When an algorithm returns the largest number 99 percent of the time but fails 1% of the time and returns the smallest number instead, it’s rarely useful. Simply put, an algorithm is a series of instructions for obtaining a result from a set of inputs. In today’s world, encryption has almost become a norm for every application.
ExamplesThere are a few algorithms that appear over and over again. We’ll look at three of the most popular in this tutorial: searching, sorting and adding to/removing from a linked list. Understanding these three examples will help us lay a stable basis on which we can confidently tackle potential algorithm problems!
Binary searchBinary search is a simple search algorithm that takes a sorted array as input and returns the index of the value we’re looking for. We accomplish this by taking the following steps:
- Find the sorted array’s midpoint.
- Compare the midpoint to the interest rate.
- Perform a binary check on the right half of the array if the midpoint is greater than the value.
- Perform a binary check on the left half of the array if the midpoint is less than the value.
- Repeat these steps until the midpoint value equals the value of interest or until we know the value isn’t in the array.
Merge SortTo sort arrays efficiently, merge sort uses a similar “divide and conquer” technique. To see how merge sort is implemented, follow the steps below.
- Return true if the array has only one element and is already sorted.
- Divide the list into halves until it can no longer be divided.
- Until we have our original sorted array, combine smaller arrays in sorted order.
Adding and Removing From a Linked ListThe linked list is a basic data structure in computer science that is especially useful for its constant-time insertion and deletion. We can perform certain processes much more quickly with nodes and pointers than we could with an array. A linked list consists of nodes, each containing data and a pointer to the next node. We can remove items from the center of a set with a linked list instead of moving the remainder of the data structure in memory, as we would with an array. We will achieve optimum productivity by selecting the right data structure for our needs!
Use of algorithmAlgorithms have the ability to save lives, make things smoother, and bring order to chaos. However, experts are concerned that they may place too much power in the hands of companies and governments, perpetuating prejudice, creating filter bubbles, limiting options, innovation, and serendipity, and possibly leading to increased unemployment. The overall effect of ubiquitous algorithms is currently incalculable. All of our extended thinking systems (algorithms power the software and communication that allow extended thinking systems) necessitate more thinking, not less, and a broader perspective than we have previously been able to achieve. Expanding data collection and analysis and the application of that data will cure illnesses, alleviate poverty, provide timely solutions to people and places in need, and dispel decades of bias and mistaken assumptions.
Maths behind algorithmsMachine learning algorithms are built so that they learn from their mistakes and enhance their performance as they consume more data. Every algorithm learns and predicts data in its own unique way. The workings of several machine learning algorithms and some of the mathematical equations used in such algorithms aid learning.
Linear RegressionBy fitting the best line on the data points, linear regression is used to predict a continuous variable’s outcome. A relationship between the dependent and independent variables is described by the best-fitted line (s). The algorithm seeks out the best-fitting line for predicting the target variable’s value. The best-fit line is found by minimizing the number of squared differences between the data points and the regression line.
Equation: Y = c + m₁X₁ + m₂X₂ + ….. +mnXn
Y → Dependent Variable or Target Variable
m → Slope
c → Intercept
X → Independent Variables