Section 1 : Introduction

Lecture 1 Welcome to the course! copy 1:38
Lecture 2 BONUS Learning Paths Pdf
Lecture 3 Where to get the materials Pdf

Section 2 : Breast Cancer Classification

Lecture 4 Introduction 0:39
Lecture 5 Business Challenge 2:45
Lecture 6 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM Pdf
Lecture 7 Challenge in Machine Learning Vocabulary
Lecture 8 Data Visualisation 16:48
Lecture 9 Model Training 8:0
Lecture 10 Model Evaluation 10:6
Lecture 11 Improving the Model 21:54
Lecture 12 Conclusion 2:39

Section 3 : Fashion Class Classification

Lecture 13 Business Challenge 4:33
Lecture 14 Challenge in Machine Learning Vocabulary 6:4
Lecture 15 Data Visualisation 15:19
Lecture 16 Model Training Part I 8:0
Lecture 17 Model Training Part II 6:59
Lecture 18 Model Training Part III 9:54
Lecture 19 Model Training Part IV 15:11
Lecture 20 Model Evaluation 8:53
Lecture 21 Improving the Model
Lecture 22 Conclusion

Section 4 : Directing Customers to Subscription Through App Behavior Analysis

Lecture 23 Fintech Case Studies Introduction 1:42
Lecture 24 Introduction 2:14
Lecture 25 Data 3:53
Lecture 26 Features Histograms 9:47
Lecture 27 Correlation Plot 5:17
Lecture 28 Correlation Matrix 7:3
Lecture 29 Feature Engineering - Response
Lecture 30 Feature Engineering - Screens 9:58
Lecture 31 Data Pre-Processing 10:21
Lecture 32 Model Building 12:54
Lecture 33 Model Conclusion 4:0
Lecture 34 Final Remarks 2:9

Section 5 : Minimizing Churn Rate Through Analysis of Financial Habits

Lecture 35 Introduction 2:13
Lecture 36 Data 8:16
Lecture 37 Data Cleaning 5:0
Lecture 38 Features Histograms 9:20
Lecture 39 Pie Chart Distributions 9:57
Lecture 40 Correlation Plot 8:14
Lecture 41 Correlation Matrix 9:30
Lecture 42 One-Hot Encoding 6:26
Lecture 43 Feature Scaling & Balancing 11:8
Lecture 44 Model Building 8:26
Lecture 45 K-Fold Cross Validation 4:44
Lecture 46 Feature Selection 7:54
Lecture 47 Model Conclusion 4:48
Lecture 48 Final Remarks 2:43

Section 6 : Predicting the Likelihood of E-Signing a Loan Based on Financial History

Lecture 49 Introduction 7:48
Lecture 50 Data 8:11
Lecture 51 Data Housekeeping 5:34
Lecture 52 Histograms 10:9
Lecture 53 Correlation Plot
Lecture 54 Correlation Matrix 7:5
Lecture 55 Feature Engineering 5:11
Lecture 56 Data Preprocessing 9:48
Lecture 57 Model Building Part 1 7:29
Lecture 58 Model Building Part 2 10:12
Lecture 59 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM Pdf
Lecture 60 Grid Search Part 2 9:50
Lecture 61 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM Pdf
Lecture 62 Final Remarks 3:31

Section 7 : Credit Card Fraud Detection

Lecture 63 Case Study 3:23
Lecture 64 Machine Learning Vocabulary 3:2
Lecture 65 Set Up 2:57
Lecture 66 Data Visualization 3:7
Lecture 67 Data Preprocessing 4:21
Lecture 68 Deep Learning Part 1 3:45
Lecture 69 Deep Learning Part 2 7:11
Lecture 70 Splitting the Data 6:6
Lecture 71 Training 2:52
Lecture 72 Metrics 3:48
Lecture 73 Confusion Matrix 5:29
Lecture 74 Machine Learning Classifiers 7:35
Lecture 75 Random Forest 3:46
Lecture 76 Decision Trees 2:51
Lecture 77 Sampling 2:4
Lecture 78 Undersampling 5:15
Lecture 79 Smote 3:45
Lecture 80 Final remarks 2:38