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31 Artificial Neural Networks.rar
505.95MB
02 -------------------- Part 1 Data Preprocessing --------------------.rar
236.33MB
03 -------------------- Part 2 Regression --------------------.rar
1.02KB
04 Simple Linear Regression.rar
200.91MB
05 Multiple Linear Regression.rar
366.21MB
06 Polynomial Regression.rar
317.15MB
07 Support Vector Regression (SVR).rar
120MB
08 Decision Tree Regression.rar
120.14MB
09 Random Forest Regression.rar
111.63MB
10 Evaluating Regression Models Performance.rar
67.89MB
11 -------------------- Part 3 Classification --------------------.rar
1.03KB
12 Logistic Regression.rar
271.64MB
13 K-Nearest Neighbors (K-NN).rar
111.02MB
14 Support Vector Machine (SVM).rar
118.49MB
15 Kernel SVM.rar
169.51MB
16 Naive Bayes.rar
176.83MB
17 Decision Tree Classification.rar
124.51MB
18 Random Forest Classification.rar
144.94MB
19 Evaluating Classification Models Performance.rar
42.5MB
20 -------------------- Part 4 Clustering --------------------.rar
1.01KB
21 K-Means Clustering.rar
141.32MB
22 Hierarchical Clustering.rar
169.91MB
23 -------------------- Part 5 Association Rule Learning --------------------.rar
906B
26 -------------------- Part 6 Reinforcement Learning --------------------.rar
1.09KB
27 Upper Confidence Bound (UCB).rar
300.34MB
28 Thompson Sampling.rar
163.29MB
29 -------------------- Part 7 Natural Language Processing --------------------.rar
448MB
30 -------------------- Part 8 Deep Learning --------------------.rar
25.49MB
01 Welcome to the course.rar
118.26MB
32 Convolutional Neural Networks.rar
353.53MB
33 -------------------- Part 9 Dimensionality Reduction --------------------.rar
1.24KB
34 Principal Component Analysis (PCA).rar
194.68MB
35 Linear Discriminant Analysis (LDA).rar
114.29MB
37 -------------------- Part 10 Model Selection Boosting --------------------.rar
1.14KB
38 Model Selection.rar
167.45MB
40 Bonus Lectures.rar
2.53KB
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