Density Estimation is an essential part of both machine learning and statistics. It means getting the probability density function (PDF) of a group. It is necessary for many things, like finding outliers, putting things into groups, making models, and finding problems. Based on deep learning, this study looks at all the ... Read More

Transformer models have progressed much in natural language processing (NLP), getting state-of-the-art results in many tasks. But Transformers' computational complexity and memory needs increase by a factor of four with the length of the input sequence. This makes it hard to handle long sequences quickly. Researchers have developed Sparse Transformers, ... Read More

This tutorial will take a wine quality dataset from online sources such as Kaggle. The preferred dataset is the "Wine Quality Dataset, " available at "https://www.kaggle.com/datasets/yasserh/wine-quality-dataset." The dataset contains a .csv file comprising various categories of wine, such as 'fixed acidity, ' 'volatile acidity, ' 'pH, ' 'density, ' and ... Read More

Introduction The brain is the most complicated organ and is used for various scientific studies. The human brain is studied and the prototype is implemented for artificial intelligence (AI) and machine learning (ML). The hippocampus is an essential part of the brain. It helps us learn, remember, and find our ... Read More

Introduction Creating realistic artificial data has become increasingly important in recent years, thanks to the wealth of extensive datasets and advancements in machine learning techniques. Traditional methods like data enrichment and sampling fall short in accurately capturing the complexity and diversity of real-world situations. However, the Factorized Random Synthesizer (FRS) ... Read More

Steady State Genetic Algorithm (SSGA) is often used in machine learning and optimization tasks. It is a population-based, iterative search method based on the ideas behind natural evolution and genetics. SSGA works with a group of possible answers, shown as people or chromosomes. Here's how SSGA genetic Algorithm works ... Read More

The Simple Genetic Algorithm (SGA) is a popular optimization method in machine learning and artificial intelligence. Modeled after natural selection, SGAs use genetic operators like crossover and mutation to create a pool of candidate solutions. They have global search capabilities and are experts in resolving complex optimization problems. SGAs help ... Read More

Optimization of Grey Wolf or GWO is a nature-inspired algorithm developed by Mirjalili et al. in 2014. Its hunting techniques and social structure are based on those of grey wolves. The algorithm is based on the concept of delta, gamma, beta and alpha wolves, representing the best solution candidates at ... Read More

Model validation is a crucial step in the machine learning process. It ensures that the models built are correct, reliable, and able to work well with data they haven't seen before. Y Scrambling is a new method that has become popular recently because it improves the confirmation process. This study ... Read More

Introduction to Attention Mechanisms Attention mechanisms are often used in machine learning to improve the performance of models that only need attention to certain parts of the data they are given. They were first used to translate words from one language to another with a machine. Instead of putting the ... Read More