Fraud Detection using Python

سرفصل های دوره

Build an effective machine learning project to detect instances of financial crime.

1. Introduction to the course

1. Our exciting Fraud Detection project demo!

2. Installing the required software.html

2. Introduction to Fraud Detection

1. What is Anomaly Detection

2. What is Fraud Detection

3. Exploring the Credit Card Fraud Data Set

4. Managing Labels in a Fraud Detection Context

5. Sampling with a Class Imbalance

6. Introduction to Fraud Detection Quiz.html

3. Training a Supervised Learning Model

1. Training a Baseline Logistic Regression Model using scikit-learn

2. Improving the Logistic Regression Model through Hyperparameter Selection

3. Interpreting the Logistic Regression Model

4. Training an XGBoost Model

5. Improving the XGBoost Model through Hyperparameter Selection

6. Interpreting the XGBoost Model

7. Training a Supervised Learning Model Quiz.html

4. Performance Metrics for Fraud Detection

1. Understanding the Cost of Misclassification

2. The Accuracy Paradox

3. Implementing Performance Metrics in scikit-learn

4. Performance Metrics for Fraud Detection Quiz.html

5. Optimal Model Selection

1. Threshold Optimization using Performance Metrics

2. Threshold Optimization using Total Cost of Fraud

3. Introduction to Streamlit

4.1 app.zip

4.2 error_df.csv

4.3 eval.zip

4. Building a Threshold Simulation for Visual Inspection

5. Optimal Model Selection Quiz.html

6. Strategies for Improving Model Performance

1. Up-sampling the Minority Class with SMOTE

2. Strategies for Improving Model Performance Quiz.html

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تولید کننده: Udemy-Training