Machine Learning

SVM  Efficient optimization with SMO algorithm Support Vector Machines Topics Separating data with the maximum margin Finding the maximum margin, Efficient optimization with SMO algorithm Speeding up optimization with full Platt SMO Using Kernels for More Complex Data Dimensionality Reduction Techniques: Principal Component analysis What is Support Vector Machines (SVM)? SVM is a type of machine learning algorithm that finds a hyperplane in a high-dimensional space to maximize the margin between the classes. 

Regression, Decision Trees  and Random Forests   Supervised Learning Concepts Linear Regression Logistic Regression Decision Trees and Random Forests Naive Bayes k-Nearest Neighbors (k-NN) Support Vector Machines (SVM) Gradient Boosting and AdaBoost                                         What is Supervised Learning? Supervised learning is a type of machine learning where the algorithm is trained on labelled data to predict future outcomes accurately .