You will get Streamlit Application for Credit Card Fraud Detection
Project details
Objective
The main goal of this project was to build a machine learning model capable of detecting fraudulent credit card transactions with high accuracy, while minimizing false positives and false negatives.
Approach
1. Data Collection and Preprocessing
I began by exploring and cleaning the dataset, handling missing values, and preparing the data for analysis to ensure reliability and consistency.
2. Data Analysis and Visualization
Through exploratory data analysis (EDA) using visualizations and statistical insights, I identified the key patterns and features distinguishing fraudulent transactions from legitimate ones.
3. Modeling
I implemented a Random Forest Classifier to train the model and evaluated its performance using metrics such as Precision, Recall, and ROC-AUC Score.
4. Evaluation and Optimization
The results were highly encouraging, achieving strong precision and maintaining a good balance between recall and accuracy in detecting fraudulent cases.
The main goal of this project was to build a machine learning model capable of detecting fraudulent credit card transactions with high accuracy, while minimizing false positives and false negatives.
Approach
1. Data Collection and Preprocessing
I began by exploring and cleaning the dataset, handling missing values, and preparing the data for analysis to ensure reliability and consistency.
2. Data Analysis and Visualization
Through exploratory data analysis (EDA) using visualizations and statistical insights, I identified the key patterns and features distinguishing fraudulent transactions from legitimate ones.
3. Modeling
I implemented a Random Forest Classifier to train the model and evaluated its performance using metrics such as Precision, Recall, and ROC-AUC Score.
4. Evaluation and Optimization
The results were highly encouraging, achieving strong precision and maintaining a good balance between recall and accuracy in detecting fraudulent cases.
Programming Languages
PythonCoding Expertise
DesignWhat's included
| Service Tiers |
Starter
$40
|
Standard
$80
|
Advanced
$120
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 8 days |
Number of Revisions | 1 | 1 | 1 |
Number of Pages | 1 | 3 | 3 |
Design Customization | - | - | - |
Content Upload | - | - | - |
Responsive Design | - | - | - |
Source Code | - | - |
About Sofiane
Data Analyst (Python & Power BI)
Boumerdas, Algeria - 8:47 pm local time
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After purchasing the project, send requirements so Sofiane can start the project.
Delivery time starts when Sofiane receives requirements from you.
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Revisions may occur after the delivery date.
développé l'application comme un model correspond a l'analyse des données
développé l'application comme un model correspond a l'analyse des données comme une présentation des étapes de l'analyse