When a text string is entered or given as input, it may have commas in between. Sometimes the task is to separate all the comma-separated portions of a sentence or a text string. These portions may have single word or multiple words. These string portions may be further entered as items of list or can be processed further. Similarly, numbers in integer form or decimal form are also needed to be entered while being separated by commas. In such cases, understanding these as numbers is important. By using four different examples, this process of given comma separated string or sentence, ... Read More

Introduction Normalization and standardization are two commonly utilized strategies in information per−processing, pointing to convert crude information into a reasonable arrange for investigation and modeling. These strategies play a crucial part in machine learning by progressing the properties of the information, such as its run, dissemination, and scale. Normalization includes scaling the information to a particular run, ordinarily between and 1, whereas protecting the relative connections between highlights. Standardization, on the other hand, centers the information on its cruelty and scales it to have a standard deviation of 1. In this article, we are going investigate the concepts of normalization ... Read More

Introduction The Perceptron Algorithm, a foundation of artificial intelligence and machine learning, shapes the premise for different complex neural network designs. In this article, we investigate the application of the Perceptron Calculation to actualize the AND logic gate with 2−bit binary inputs. The AND gate, a principal parallel logic gate, produces a 1 yield as it were when both inputs are 1; something else, the yield is 0. Through a step−by−step clarification of the Perceptron Algorithm and Python code execution, we reveal how this calculation can be prepared to imitate the behavior of the AND gate. Understanding the AND Logic ... Read More

Introduction Linear algebra forms the backbone of many machine learning algorithms, and one key concept within this field is that of basis vectors. In machine learning, basis vectors provide a powerful framework for representing and understanding complex data sets. By decomposing data into its constituents based on these vectors, we unlock new ways to extract meaningful patterns and make accurate predictions. This article explores the role of basis vectors in linear algebra's application to machine learning. Understanding how to leverage basis vectors empowers researchers and practitioners to push the boundaries of machine learning, ultimately leading us towards smarter technologies ... Read More

Introduction The concept of randomness plays a crucial part in different areas such as insights, cryptography, and simulation. Deciding whether a sequence of information is really irregular or shows a few basic designs is fundamental in numerous applications. One measurable test commonly utilized for this reason is the Runs test of randomness. In this article, we dig into the Runs test of randomness and illustrate how to perform it utilizing Python, a flexible programming language broadly utilized for factual examination. By leveraging the capable capabilities of Python and the scipy.stats module, able to efficiently apply the Runs test to ... Read More

Introduction Within the domain of decision−making, there are often multiple criteria that have to be considered at the same time. Whether it's selecting an unused item to dispatch, choosing a venture procedure, or making an individual choice, assessing and positioning choices based on different components can be a complex assignment. Multi−Criteria Decision Making (MCDM) strategies offer an organized approach to handling such issues. One such strategy is the Weighted Product Method (WPM), which gives an orderly way of consolidating preferences and weighting criteria to reach at the last choice. In this article, we'll dig into the complexities of the Weighted ... Read More

A number is said to be a Strong number if the factorials of its individual digits are found and then added together and the total sum calculated is equal to the number itself. Here, in this Python article, using three different examples, the different methods of finding the Strong numbers if present in a list are given. In the Example 1, a list that contains the precalculated factorials of numbers are used for calculating the sum of factorials of all the present digits in a number while checking whether the selected number is strong or not. In example 2, the ... Read More

Sometimes the task is to select only the positive numbers from a given range. Here, in this Python article, first, the range is taken as input and then the negative as well as positive integers within this range are chosen. In this Python article, from these numbers only the positive numbers are then selected using the different methods in four different examples. In example 1, the positive numbers are picked and separated into another list. In the example 2, all the elements that are not positive are removed. In example 3, the sorted list is split up to zero and ... Read More

Introduction Artificial intelligence and machine learning have experienced a transformation since to Deep Neural Networks (DNN), which have empowered exceptional progressions over a assortment of areas. In this article, we'll look at the thoughts of forward and backward propagation and how they relate to the advancement and advancement of advanced neural systems. Python librariеs likе TеnsorFlow havе incredibly streamlined thе execution of thе systеms, making thеm morе opеn to analysts and professionals. Approach 1 : Tensorflow In this approach, we utilize the control of the TensorFlow library to execute a profound neural arrange with forward and backpropagation. ... Read More

Sometimes the task is to select the negative numbers from a given range. Here, in this Python article, first, the range is taken as input and then the integers within this range are specified. From these numbers only the negative numbers are then selected using the different methods in 4 different examples. In example 1, the negative numbers are picked and separated into another list. In the example 2, all the elements that are not negative are removed. In example 3, the sorted list is split upto zero and only negatives are retained. In example 4, filter is used to ... Read More