In this post, we will examine the differences between thick and thin clients and examine how they function. College students with technical expertise will also find this essay to be very valuable because they may use it as a test question. The primary difference between the two is that a distant laptop executes apps for the thin client. However, the thick client processes the software while the apps are being used locally. The distinctions between slim and overweight clients will also be substantial. Before contrasting clients who are thin and fat, let's define the term "client." Was that supposed to ... Read More

We are aware that every business has a unique operating system, and the same is true of every commercial endeavor. On the other hand, if your processes involve repeated computer−related tasks, an entire automation solution powered by RPA bots may be a good fit. RPA enables you to keep all of your jobs and data in−house, which lowers costs and increases output. The following list of business sectors and office functions that are amenable to automation The main way we differ from other companies is that we will work with you to identify the process that is best suited for ... Read More

In application modeller, element mask−which enables you to replicate the attribute selection of one element and apply it to others−is the way of the future. You may determine which characteristics should be used by various application model components (eg. Class Name, Window Text, W and Z). This may be done by creating an element with the required characteristics, copying and pasting the element's "Element Mask, " and then creating the extra elements. This will allow the same attributes in the target element that are enabled in the source element and set the match types (Equals, Greater Than, etc.) to the ... Read More

In this article, we are going to learn about the difference between – Training, Testing, and Validation sets Introduction Data splitting is one of the simplest preprocessing techniques we can use in a Machine Learning/Deep Learning task. The original dataset is split into subsets like training, test, and validation sets. One of the prime reasons this is done is to tackle the problem of overfitting. However, there are other benefits as well. Let's have a brief understanding of these terms and see how they are useful. Training Set The training set is used to fit or train the model. These ... Read More

In this article, let’s explore 7 such areas which are promising and booming in 2022 related to Artificial Intelligence. Introduction Over the last decade, we saw tremendous growth and development in Artificial Intelligence-related technologies in almost every domain and is still becoming more relevant in the current era or decade. There have been ground-breaking research in AI and ML which has changed the current scenario of how we pursue technology infused with machine intelligence.AI related technology has found application in every domain. To name a few like Healthcare, Cybersecurity, HR Processes, Space exploration, and many more. Trends in 2022 1. ... Read More

Introduction Regression Analysis is the most basic form of predictive analysis. In Statistics, linear regression is the approach of modeling the relationship between a scalar value and one or more explanatory variables. In Machine learning, Linear Regression is a supervised algorithm. Such an algorithm predicts a target value based on independent variables. More About Linear Regression and Regression Analysis In Linear Regression / Analysis the target is a real or continuous value like salary, BMI, etc. It is generally used to predict the relationship between a dependent and a bunch of independent variables. These models generally fit a linear equation, ... Read More

Introduction One of the most common tasks involved in Deep Learning based on Image data is Image Classification. Image classification has become more interesting in the research field due to the development of new and high-performing machine learning frameworks. Such classification can either be binary where two classes of images are present or multiclass classification which deals with more than two image classes. Here, in this article, we are going to explore transfer learning with multiclass image classification. Multiclass Image Classification With the advancement in artificial Neural networks and the development of Convolutional Neural Networks complex operations on images have ... Read More

In this tutorial, we are going to learn about how to handle imbalanced classes in ML. Introduction Generally speaking, class imbalance in Machine Learning is a case where classes of one type or observation are higher as compared to the other type. It is a common problem in Machine learning involving tasks such as fraud detection, ad click averts, spam detection, consumer churn, etc. It has a high effect on the accuracy of the model. Effects of Class Imbalance In case of such problems, the majority class overpowers the minority class while training the model. Since in such cases, one ... Read More

This article let us see some of the common challenges Machine Learning Engineers face today. Introduction Today when Machine Learning has become the cutting-edge technology in every domain or industry, the number of Machine Learning folks has considerably grown and so is the challenge to implement an Artificial Intelligence project from start to finish, from drafting the concept to bringing the concept to production. The path of a Machine Learning Engineer is not easy as he /she faces numerous challenges along this path. Collection of Good Quality Data Yes, this is true. We cannot deny the fact that today data ... Read More

In this article we are going to learn how to predict stock price direction using Support Vector Machines. Machine Learning is an Artificial Intelligence application that is improving the way the world functions in every discipline. At its essence, it is an algorithm or model that identifies patterns in a specific data collection and then predicts the learned patterns on generic data. In layman's words, it's the concept that robots learn a pattern and adjust through experience to make correct and repeatable conclusions. In this post, we will look into Predicting Stock Price Direction Using Support Vector Machines. Let’s begin. ... Read More