Found 145 Articles for Gadgets

The IoT has been connected with significant cyberattacks, including the abuse of pitifully related gadgets, similar to perception cameras, to work with poisonous activities. Concerns have been raised about the IoT's capacity to get billions of gadgets related to the abnormal web, calling for appropriate courses of action that could fill the security opening. Here enters the blockchain, an early development that promises to diminish the bet of IoT contraptions being yielded through a central power and to chip away at the flexibility of IoT executions. IoT Definition The IoT biological system is an organization of interconnected gadgets that permit ... 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

Artificial intelligence (AI) is the capacity of a machine created artificially to think and act logically or human-like. The study of the rational agent and its surroundings can be used to define an AI system. Agents use sensors to perceive their surroundings and actuators to take action on it. Knowledge, belief, purpose, and other mental attributes can exist in an AI agent. AI agents are directly related to PEAS. In this piece, we'll take a closer look at PEAS and some of its examples. What are PEAS Descriptors? PEAS is an AI agent representation system that focuses on evaluating the ... Read More

Data preparation is a necessary step before modeling in the field of data science. We must do a number of activities during the data preparation process. One such important task is encoding categorical data. As is well known, the majority of data in the real world has categorical string values, while the majority of machine learning models only operate with integer values. However, certain models can work with other values that are more complex but still intelligible to the model. In essence, all models carry out mathematical operations that can be done with a variety of tools and approaches. But ... Read More