Machine Learning (ML) Regression dilution In this article at OpenGenus, we will explore the concept of regression dilution, its implications in various real-world applications. We will discuss when it is crucial to correct for these errors and when it may be appropriate to skip correction.
Algorithms Solving Course Scheduling Problem using Topological Sort In this article at OpenGenus, we will solve the famous course scheduling problem and it's variations using the graph algorithm known as Topological Sort.
C++ How to Use Friend Classes in C++ to Access Private and Protected Members In this article at OpenGenus, we will be going over friend classes in C++, what they're used for, usage examples, difference between friendship and inheritance, and alternatives.
Python How to make a click logger [with Python code] In this article at OpenGenus, we will make a program that tracks the active windows in your laptop that you click on and prints their names on the terminal. This is program is just for education purposes.
Algorithms Legendre and His Formula: Speeding Up Factorial Calculations Factorial calculations are a fundamental mathematical operation in computer science, commonly used in algorithms and equations. The factorial of a non-negative integer 'n' is defined as the product of all positive integers from 1 to 'n.'
Algorithms Finding Exponent of a Number [5 approaches] Exponent is a method of expressing large numbers in terms of powers. It refers to how many times a number is multiplied by itself.
C++ Lazy initialization in C++ Lazy initialization is a technique where the creation of an object is deferred until it is actually needed. This can improve performance by avoiding the creation of objects that are never used.
Algorithms Ceiling in a Sorted Array You are given a sorted array of integers and a target value 'x'. Your task is to find the lower bound, which is the smallest element in the array that is greater than or equal to 'x'.
Java Difference between java, javaw, javaws and javac In this article at OpenGenus, we will learn about difference between java, javaw, javaws and javac in Java Programming Language.
Software Engineering Amdahl’s law Amdahl's law was presented by a computer scientist named Gene Amdahl at the American Federation of Information processing Societies (AFIPS) Spring Joint Computer conference in 1967, From there it got its name.
Machine Learning (ML) Demystifying Kernel Density Estimation (KDE) in Python In this article at OpenGenus, we will start by a general and a mathematical understanding of Kernel Density Estimation and then after exploring some applications of KDE, we, stepwise, implement it in Python.
Algorithms Next Greater Frequency Element This problem involves combining the concepts of frequency counting and stack-based processing to efficiently determine the next element with a higher frequency for each element in the array.
Deep Learning ML model to predict Fuel Efficiency [project] The goal of the fuel efficiency project at OpenGenus is to predict the fuel efficiency of a vehicle based on various input features.
System Design Pareto Principle in Computer Science and Software Development In this article at OpenGenus, we'll explore how the Pareto Principle is applied in these fields, delve into the concept of the Pareto Distribution, and discuss its profound significance in the realm of software development.
Operating System Paging in OS: Enhancing Memory Management In this article at OpenGenus, we explore paging which can fix the issues that many users face without even realizing it - the absence of an essential memory management technique.
Software Engineering Trading Application in C++ [Software Development Project with source code] A Trading App, sometimes called a stock trading or investment app, is a handy tool that allows people to easily buy, sell, and manage various types of financial assets like stocks, bonds, cryptocurrencies, and commodities using their smartphones or tablets.
Deep Learning MobileNet V3 model MobileNetV3 is a neural network architecture designed to provide efficient deep learning capabilities on resource-constrained mobile devices. We delve into the essence of MobileNetV3, exploring its history, applications, advantages, disadvantages, and underlying architecture.
Deep Learning Cold start and Data sparsity problem in Recommender system Recommender systems are commonplace in the modern digital era and shape our online experiences by recommending movies, goods, and information based on our tastes. However, the Cold Start Problem and Data Sparsity are two key issues that frequently plague these systems.
System Design Canary and Rolling Deployments strategies explained A deployment strategy is a way to change or upgrade an application with the aim of no perceptible downtime i.e. Rolling and Canary Deployment.
Algorithms Minimize Maximum Distance between Gas Stations [Solved 3 approaches] You are given a sorted array ‘arr’ of length ‘n’, which contains positive integer positions of ‘n’ gas stations on the X-axis. You are also given an integer ‘k’. You have to place ‘k’ new gas stations on the X-axis.
Python Streamlit library in Python [Practical Introduction] Streamlit is a Python library that enables us to quickly build front-end web pages for our data application by using just Python codes.
Web Development Web Video Text Tracks Format (WebVTT): for adding Video Subtitles WebVTT is a format for HTML5 video captions, subtitles and overlays. It is a text file with timed cues, and it starts with a WebVTT body. Cues display text at specific times, while comments are added as notes.
kotlin JvmStatic, JvmOverloads and JvmFields Annotations in Kotlin In Kotlin Programming language, @JvmOverloads, @JvmField, and @JvmStatic are annotations used for improving the interoperability with the Java code.
Deep Learning Concept and Data Drift in Deep Learning "Drift" is a concept frequently employed in machine learning to delineate the gradual deterioration in the operational efficacy of a machine learning model over an extended period.
Deep Learning Polyak Averaging Polyak averaging is named after its inventors Anatoli Juditsky and Arkadii Nemirovski (also known as Polyak and Ruppert) and is a method of model averaging that helps to produce a more robust and accurate final model by combining the information from different iterations.
