Introduction to Neural Networks
A Neural Network is a computational model inspired by the human brain. It consists of layers of interconnected neurons that process input data to learn patterns and make predictions. Neural….
Tag: AI
Reinforcement Learning Basics
Reinforcement Learning Basics: A Detailed Overview Reinforcement Learning (RL) is a type of machine learning where an agent learns how to behave in an environment by performing actions and receiving….
Generative Adversarial Networks (GANs)
Generative Adversarial Networks (GANs): A Comprehensive Overview Generative Adversarial Networks (GANs) have revolutionized the field of machine learning by offering a way to generate realistic data, including images, text, and….
Recurrent Neural Networks (RNNs)
Recurrent Neural Networks (RNNs): Detailed Explanation Recurrent Neural Networks (RNNs) are a class of neural networks designed for processing sequences of data. Unlike traditional feedforward neural networks, RNNs are designed….
DBSCAN Clustering
DBSCAN Clustering: A Comprehensive Guide 1. Introduction to DBSCAN DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is an unsupervised machine learning clustering algorithm that groups together points that are….
Gaussian Mixture Models
Gaussian Mixture Models (GMM) – A Comprehensive Guide 1. Introduction to Gaussian Mixture Models (GMM) A Gaussian Mixture Model (GMM) is a probabilistic clustering algorithm based on the assumption that….
K-Means Clustering
K-Means Clustering: A Comprehensive Guide 1. Introduction to K-Means Clustering K-Means Clustering is an unsupervised machine learning algorithm used for grouping similar data points into clusters. It aims to partition….
Gradient Boosting (XGBoost, LightGBM, CatBoost)
Gradient Boosting (XGBoost, LightGBM, CatBoost) in Machine Learning 1. Introduction to Gradient Boosting Gradient Boosting is a powerful ensemble learning technique used in machine learning for classification and regression tasks…..
Naïve Bayes Classifier
Naïve Bayes Classifier in Machine Learning 1. Introduction to Naïve Bayes Classifier The Naïve Bayes (NB) classifier is a probabilistic machine learning algorithm used for classification tasks. It is based….
k-Nearest Neighbors (k-NN)
k-Nearest Neighbors (k-NN) Algorithm in Machine Learning 1. Introduction to k-Nearest Neighbors (k-NN) k-Nearest Neighbors (k-NN) is a supervised learning algorithm used for classification and regression tasks. It is a….