You will get Fraud Detection using Logistic Regression
Project details
This project develops a fraud detection model using machine learning techniques to identify suspicious transactions. It includes data exploration, preprocessing, model training, and performance evaluation. The final result is a well-documented solution with clear visualizations and organized code that helps understand and detect fraudulent activity effectively.
Machine Learning Tools
NumPy, Python, scikit-learnWhat's included
| Service Tiers |
Starter
$10
|
Standard
$20
|
Advanced
$50
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 2 | 4 | 6 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
About Mohammed Adel
AI & Machine Learning | Artificial Intelligence, Machine Learning
Alexandria, Egypt - 3:35 pm local time
My journey at university has been enriched by hands-on projects and coursework, where I've gained proficiency in Python, TensorFlow, and PyTorch, particularly in developing embedded AI systems. I am driven by the transformative potential of AI, from crafting innovative IoT devices to enhancing NLP applications. If you're seeking a forward-thinking collaborator who can bring fresh ideas and a solid technical foundation to your project, I'm eager to connect and discuss how I can contribute to your vision.
Steps for completing your project
After purchasing the project, send requirements so Mohammed Adel can start the project.
Delivery time starts when Mohammed Adel receives requirements from you.
Mohammed Adel works on your project following the steps below.
Revisions may occur after the delivery date.
Data Analysis
Analyze the dataset, explore features and clean the data to prepare it for building the fraud detection model.