Section 1 : Introduction
Lecture 1 Welcome to the course! copy 00:01:38 Duration
Lecture 2 BONUS Learning Paths
Lecture 3 Where to get the materials

Section 2 : Breast Cancer Classification
Lecture 1 Introduction 00:00:39 Duration
Lecture 2 Business Challenge 00:02:45 Duration
Lecture 3 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM
Lecture 4 Challenge in Machine Learning Vocabulary
Lecture 5 Data Visualisation 00:16:48 Duration
Lecture 6 Model Training 00:08:00 Duration
Lecture 7 Model Evaluation 00:10:06 Duration
Lecture 8 Improving the Model 00:21:54 Duration
Lecture 9 Conclusion 00:02:39 Duration

Section 3 : Fashion Class Classification
Lecture 1 Business Challenge 00:04:33 Duration
Lecture 2 Challenge in Machine Learning Vocabulary 00:06:04 Duration
Lecture 3 Data Visualisation 00:15:19 Duration
Lecture 4 Model Training Part I 00:08:00 Duration
Lecture 5 Model Training Part II 00:06:59 Duration
Lecture 6 Model Training Part III 00:09:54 Duration
Lecture 7 Model Training Part IV 00:15:11 Duration
Lecture 8 Model Evaluation 00:08:53 Duration
Lecture 9 Improving the Model
Lecture 10 Conclusion

Section 4 : Directing Customers to Subscription Through App Behavior Analysis
Lecture 1 Fintech Case Studies Introduction 00:01:42 Duration
Lecture 2 Introduction 00:02:14 Duration
Lecture 3 Data 00:03:53 Duration
Lecture 4 Features Histograms 00:09:47 Duration
Lecture 5 Correlation Plot 00:05:17 Duration
Lecture 6 Correlation Matrix 00:07:03 Duration
Lecture 7 Feature Engineering - Response
Lecture 8 Feature Engineering - Screens 00:09:58 Duration
Lecture 9 Data Pre-Processing 00:10:21 Duration
Lecture 10 Model Building 00:12:54 Duration
Lecture 11 Model Conclusion 00:04:00 Duration
Lecture 12 Final Remarks 00:02:09 Duration

Section 5 : Minimizing Churn Rate Through Analysis of Financial Habits
Lecture 1 Introduction 00:02:13 Duration
Lecture 2 Data 00:08:16 Duration
Lecture 3 Data Cleaning 00:05:00 Duration
Lecture 4 Features Histograms 00:09:20 Duration
Lecture 5 Pie Chart Distributions 00:09:57 Duration
Lecture 6 Correlation Plot 00:08:14 Duration
Lecture 7 Correlation Matrix 00:09:30 Duration
Lecture 8 One-Hot Encoding 00:06:26 Duration
Lecture 9 Feature Scaling & Balancing 00:11:08 Duration
Lecture 10 Model Building 00:08:26 Duration
Lecture 11 K-Fold Cross Validation 00:04:44 Duration
Lecture 12 Feature Selection 00:07:54 Duration
Lecture 13 Model Conclusion 00:04:48 Duration
Lecture 14 Final Remarks 00:02:43 Duration

Section 6 : Predicting the Likelihood of E-Signing a Loan Based on Financial History
Lecture 1 Introduction 00:07:48 Duration
Lecture 2 Data 00:08:11 Duration
Lecture 3 Data Housekeeping 00:05:34 Duration
Lecture 4 Histograms 00:10:09 Duration
Lecture 5 Correlation Plot
Lecture 6 Correlation Matrix 00:07:05 Duration
Lecture 7 Feature Engineering 00:05:11 Duration
Lecture 8 Data Preprocessing 00:09:48 Duration
Lecture 9 Model Building Part 1 00:07:29 Duration
Lecture 10 Model Building Part 2 00:10:12 Duration
Lecture 11 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM
Lecture 12 Grid Search Part 2 00:09:50 Duration
Lecture 13 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM
Lecture 14 Final Remarks 00:03:31 Duration

Section 7 : Credit Card Fraud Detection
Lecture 1 Case Study 00:03:23 Duration
Lecture 2 Machine Learning Vocabulary 00:03:02 Duration
Lecture 3 Set Up 00:02:57 Duration
Lecture 4 Data Visualization 00:03:07 Duration
Lecture 5 Data Preprocessing 00:04:21 Duration
Lecture 6 Deep Learning Part 1 00:03:45 Duration
Lecture 7 Deep Learning Part 2 00:07:11 Duration
Lecture 8 Splitting the Data 00:06:06 Duration
Lecture 9 Training 00:02:52 Duration
Lecture 10 Metrics 00:03:48 Duration
Lecture 11 Confusion Matrix 00:05:29 Duration
Lecture 12 Machine Learning Classifiers 00:07:35 Duration
Lecture 13 Random Forest 00:03:46 Duration
Lecture 14 Decision Trees 00:02:51 Duration
Lecture 15 Sampling 00:02:04 Duration
Lecture 16 Undersampling 00:05:15 Duration
Lecture 17 Smote 00:03:45 Duration
Lecture 18 Final remarks 00:02:38 Duration