Name                                                    Last modified      Size  
 Parent Directory                                                             -   
 06 Data Preprocessing/                                  2026-02-27 13:49    -   
 07 Linear Regression/                                   2026-02-27 13:48    -   
 08 Classification Models Data Preparation/              2026-02-27 13:46    -   
 09 The Three classification models/                     2026-02-27 13:45    -   
 10 Logistic Regression/                                 2026-02-27 13:45    -   
 11 Linear Discriminant Analysis (LDA)/                  2026-02-27 13:45    -   
 12 K-Nearest Neighbors classifier/                      2026-02-27 13:45    -   
 13 Comparing results from 3 models/                     2026-02-27 13:44    -   
 14 Simple Decision Trees/                               2026-02-27 13:44    -   
 15 Simple Classification Tree/                          2026-02-27 13:44    -   
 16 Ensemble technique 1 - Bagging/                      2026-02-27 13:43    -   
 17 Ensemble technique 2 - Random Forests/               2026-02-27 13:43    -   
 18 Ensemble technique 3 - Boosting/                     2026-02-27 13:43    -   
 19 Maximum Margin Classifier/                           2026-02-27 13:42    -   
 20 Support Vector Classifier/                           2026-02-27 13:42    -   
 21 Support Vector Machines/                             2026-02-27 13:42    -   
 22 Creating Support Vector Machine Model in Python/     2026-02-27 13:42    -   
 23 Creating Support Vector Machine Model in R/          2026-02-27 13:41    -   
 24 Introduction - Deep Learning/                        2026-02-27 13:40    -   
 25 Neural Networks - Stacking cells to create network/  2026-02-27 13:40    -   
 26 ANN in Python/                                       2026-02-27 13:39    -   
 27 ANN in R/                                            2026-02-27 13:38    -   
 28 CNN - Basics/                                        2026-02-27 13:37    -   
 29 Creating CNN model in Python/                        2026-02-27 13:36    -   
 30 Creating CNN model in R/                             2026-02-27 13:36    -   
 31 Project  Creating CNN model from scratch in Python/  2026-02-27 13:35    -   
 32 Project  Creating CNN model from scratch/            2026-02-27 13:35    -   
 33 Project  Data Augmentation for avoiding overfitting/ 2026-02-27 13:34    -   
 34 Transfer Learning  Basics/                           2026-02-27 13:34    -   
 35 Transfer Learning in R/                              2026-02-27 13:34    -   
 36 Time Series Analysis and Forecasting/                2026-02-27 13:34    -   
 37 Time Series - Preprocessing in Python/               2026-02-27 13:33    -   
 38 Time Series - Important Concepts/                    2026-02-27 13:32    -   
 39 Time Series - Implementation in Python/              2026-02-27 13:31    -   
 40 Time Series - ARIMA model/                           2026-02-27 13:30    -   
 41 Time Series - SARIMA model/                          2026-02-27 13:30    -   
 42 Bonus Section/                                       2026-02-27 13:30    -   

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