🎓 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 install Tensorflow GPU Cuda Toolkit and Keras in Anaconda Windows by Mahesh Huddar If you encounter an issue when you first import TensorFlow that starts with "A module that was compiled using NumPy 1.x cannot be run in NumPy 2.0.2 as it may crash..." Just go back to the Anaconda prompt and run pip install numpy==1.26.4 The following concepts are discussed: ______________________________ tensorflow, keras, cuda toolkit, tensorflow GPU, Install tensorflow, Install keras, Install cuda toolkit, Install tensorflow GPU, setup GPU in tensorflow, Install tensorflow on windows, Install keras on windows, Install cuda toolkit on windows, Install tensorflow GPU on windows, setup GPU in tensorflow on windows, Install tensorflow in anaconda, Install keras in anaconda, Install cuda toolkit in anaconda, Install tensorflow GPU in anaconda, setup GPU in tensorflow in anaconda ******************************** 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