Published inAI AdvancesThe Core of Decision Tree Mechanics: Impurity, Gain, and Greedy AlgorithmsExplore technical insights with practical walkthrough examples2d ago2d ago
Published inAI AdvancesOptimizing k-Nearest Neighbor in Machine LearningDistance computation and k selection strategies4d ago4d ago
Master Gradient Boosting for Powerful Machine Learning ModelsExplore core concepts and practical implementations for enhanced performance4d ago4d ago
A Comprehensive Guide on Loss Functions in Machine LearningChoosing a right loss function for your task and data6d ago6d ago
Published inLevel Up CodingBuilding Deep Feedforward NetworksDeep Dive into Feedforward Architectures with Math and Code6d agoA response icon16d agoA response icon1
Published inAI AdvancesBayesian Inference and MAP Estimation in Data Scarce ScenarioExplore Practical Applications of MAP vs. MLE in Churn PredictionJun 4A response icon2Jun 4A response icon2
Published inData Science CollectiveEnsemble Naive Bayes for Mixed Data TypesMathematical principles of Naive Bayes and applications of ensemble frameworks on diverse datasetsJun 4Jun 4
Published inLevel Up CodingBuilding a Custom Perceptron ClassifierUnpacking the math and code behind the foundational deep learning algorithmJun 1Jun 1
Solving Zero-Frequency in NLP with Smoothing TechniquesPractical applications of key smoothing algorithms in n-gram modelsJun 1Jun 1
Published inData Science CollectiveA Comprehensive Guide on Neural Network in Deep LearningUnderstanding architectures, core components, training techniques, and key differences from machine learningMay 30May 30
