Filename Size 01 Welcome to the course.rar 118.3 MB 02 -------------------- Part 1 Data Preprocessing --------------------.rar 236.3 MB 03 -------------------- Part 2 Regression --------------------.rar 1 KB 04 Simple Linear Regression.rar 200.9 MB 05 Multiple Linear Regression.rar 366.2 MB 06 Polynomial Regression.rar 317.1 MB 07 Support Vector Regression (SVR).rar 120 MB 08 Decision Tree Regression.rar 120.1 MB 09 Random Forest Regression.rar 111.6 MB 10 Evaluating Regression Models Performance.rar 67.9 MB 11 -------------------- Part 3 Classification --------------------.rar 1 KB 12 Logistic Regression.rar 271.6 MB 13 K-Nearest Neighbors (K-NN).rar 111 MB 14 Support Vector Machine (SVM).rar 118.5 MB 15 Kernel SVM.rar 169.5 MB 16 Naive Bayes.rar 176.8 MB 17 Decision Tree Classification.rar 124.5 MB 18 Random Forest Classification.rar 144.9 MB 19 Evaluating Classification Models Performance.rar 42.5 MB 20 -------------------- Part 4 Clustering --------------------.rar 1 KB 21 K-Means Clustering.rar 141.3 MB 22 Hierarchical Clustering.rar 169.9 MB 23 -------------------- Part 5 Association Rule Learning --------------------.rar 906 B 24 Apriori.rar 266.4 MB 25 Eclat.rar 42.2 MB 26 -------------------- Part 6 Reinforcement Learning --------------------.rar 1.1 KB 27 Upper Confidence Bound (UCB).rar 300.3 MB 28 Thompson Sampling.rar 163.3 MB 29 -------------------- Part 7 Natural Language Processing --------------------.rar 448 MB 30 -------------------- Part 8 Deep Learning --------------------.rar 25.5 MB 31 Artificial Neural Networks.rar 506 MB 32 Convolutional Neural Networks.rar 353.5 MB 33 -------------------- Part 9 Dimensionality Reduction --------------------.rar 1.2 KB 34 Principal Component Analysis (PCA).rar 194.7 MB 35 Linear Discriminant Analysis (LDA).rar 114.3 MB 36 Kernel PCA.rar 92.2 MB 37 -------------------- Part 10 Model Selection Boosting --------------------.rar 1.1 KB 38 Model Selection.rar 167.5 MB 39 XGBoost.rar 100.4 MB 40 Bonus Lectures.rar 2.5 KB
