🎓 Complete Machine Learning Playlist | Algorithms & Solved Examples Welcome to the Ultimate Machine Learning Playlist – a detailed collection of tutorials covering a wide range of algorithms with step-by-step solved numerical examples. Whether you're a student, a beginner, or preparing for interviews, this playlist will help you master both the concepts and practical applications. --- 📘 Algorithms & Topics Covered: 🔸 Supervised Learning 📌 Decision Trees (ID3, Gini Index, C4.5, CART, Boolean Function Trees) 📌 Naive Bayes Classifier (Laplace Correction, Text Classification) 📌 K-Nearest Neighbors (KNN with various distance metrics) 📌 Linear & Logistic Regression (Simple, Multiple, Matrix Form) 📌 Support Vector Machines (SVM, Linear/Non-Linear, Kernel Methods) 📌 Neural Networks (Perceptron, Backpropagation, MLP, RBF, Activation Functions) 🔸 Unsupervised Learning 📊 K-Means Clustering (Standard, K-Means++, Bisecting K-Means) 📊 K-Medoids Clustering 📊 Hierarchical Clustering (Single, Average, Complete Linkage) 📊 DBSCAN, EM Algorithm, DIANA Clustering 📊 Dimensionality Reduction (PCA, SVD, KL Transform) 🔸 Ensemble & Advanced Methods 🌲 Random Forest 💡 Genetic Algorithms (Selection, Crossover, Mutation) 🔍 Bayesian Belief Networks 📈 Gradient Descent (Batch, Stochastic, Delta Rule) 🧪 Feature Selection (Wrapper, Filter, Embedded) 🔸 Other Key Concepts 🧠 Overfitting & Regularization (Lasso, Ridge, Elastic Net) 🎯 ROC Curve, Confusion Matrix, Accuracy, Precision, Recall, F1 Score 🔁 Distance Measures (Euclidean, Manhattan, Minkowski, Cosine, Hamming) 📊 Outlier Detection (IQR, Z-Score, SMOTE, NearMiss, Tomek Links) 🧾 Association Rules (Apriori, ECLAT) 🧮 Case-Based Reasoning, Candidate Elimination, Find-S 💬 TF-IDF, Sentiment Analysis, One-Hot Encoding --- 📝 Why this playlist? * Covers syllabus-relevant content for B.E., M.Tech, and competitive exams * Focused on conceptual clarity and hands-on problem solving * Great for quick revisions or full-length study 🔔 Subscribe and turn on notifications to stay updated!
Curated by: Mahesh Huddar (337 videos)
How to get the best Split point or splitting point of Continuous Attribute using Entropy and Information Gain by Mahesh Huddar How to find entropy and information gain: https://www.youtube.com/watch?v=wefc_36d5mU The following concepts are discussed: ______________________________ How to get the best Split point of Continuous Attribute using Entropy and Information Gain, How to get the best Split point of Continuous Attribute, How to get the best splitting point of Continuous Attribute, How to get the best Split point, Splitting Continuous Attribute using Entropy and Information Gain ******************************** 1. Blog / Website: https://www.vtupulse.com/ 2. Like Facebook Page: https://www.facebook.com/VTUPulse 3. Follow us on Instagram: https://www.instagram.com/vtupulse/ 4. Like, Share, Subscribe, and Don't forget to press the bell ICON for regular updates