Machine Learning

🎓 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)


Currently Playing: Part 1: Plant Leaf Disease Prediction TensorFlow Keras CNN Streamlit Machine Learning Mahesh Huddar

Part 1: Plant Leaf Disease Prediction using TensorFlow Keras CNN Streamlit Machine Learning by Mahesh Huddar Download Source Code: https://www.vtupulse.com/product/plant-leaf-disease-detection-project-source-code/ Download Final Year Projects: https://vtupulse.com/download-final-year-projects/ Part 1 (Model Building): https://www.youtube.com/watch?v=148eu_foNo8 Part 2 (Streamlit Application): https://www.youtube.com/watch?v=UeKa1I2LWjc The main aim of this project is to create a convolutional neural network (CNN) that will predict whether a plant leaf is suffering from a disease or not. CNN classification model is trained, validated, and tested with different layers and other hyperparameters. CNN is built using TensorFlow and Keras. Download Final Year Projects: https://vtupulse.com/download-final-year-projects/ Final Year Projects: https://www.youtube.com/watch?v=o0PdqzRTy1g&list=PL4gu8xQu0_5ILky1wSEzplFroALOJyKdY The following concepts are discussed: ______________________________ Plant Leaf Disease Prediction, Plant Leaf Disease detection, Plant Disease detection, maize leaf disease detection, crop disease detection using machine learning, potato leaf disease detection, plant leaf disease detection using CNN, plant leaf disease detection using image processing, plant disease detecion streamlit app, streamlit app for disease, how to run a streamlit app, streamlit machine learning app ******************************** 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


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