Predictive Analytics with Machine Learning for Fraud Detection of Online Marketing Transactions
Objective
Introducing different advance technologies used to deal with frauds and threats which are happening while transaction becoming through online. feature engineering and its feature selection are including to show the better performance of the advance technologies .
Abstract
With digital strategies coping up with online marketing system, enormous data passed to these sectors, online transactions are becoming more prone to frauds and threats resulting in data leakage and personal details exposed to fraudsters leading to huge loss to customers. This makes online marketing systems adapt to high-level security and data handling technology solutions like machine learning, deep learning and predictive analytics which are efficient enough to deal with highly sensitive data, predict frauds and unwanted behavioral patterns in this data. This paper reviews the different advance technologies commonly used to deal with this type of data forms a comparison among them and suggests the most efficient and informative method to use in this sector. Through the end of the review, feature engineering and its selection of parameters for achieving better performance are discussed.
KEYWORDS: Machine Learning, online transactions,predictive analytics
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
HARDWARE SPECIFICATIONS:
- Processor- I3/Intel Processor
- RAM- 4GB (min)
- Hard Disk- 128 GB
- Key Board-Standard Window
- Keyboard. Mouse-Two or Three Button Mouse.
- Monitor-Any.
SOFTWARE SPECIFICATIONS:
- Operating System: Windows 7+
- Technology: Python 3.6+
- IDE: PyCharm IDE
- Libraries Used: Pandas, NumPy, OpenCV, TensorFlow, Matplotlib.
Learning Outcomes
- About Python.
- About PyCharm.
- About Pandas.
- About Numpy.
- About HTML.
- About CSS.
- About JavaScript.
- About Database.
- About Machine Learning.
- About Artificial Intelligent.
- About how to use the libraries.
- Project Development Skills:
- Problem analyzing skills.
- Problem solving skills.
- Creativity and imaginary skills.
- Programming skills.
- Deployment.
- Testing skills.
- Debugging skills.
- Project presentation skills.
- Thesis writing skills
Related Projects
Paper Publishing
Request Call Back
Would you like to receive a free callback now?
Choose the best time for callback:
Leave your message and we will contact you as soon as possible
Disclaimer - Takeoff Edu Group Projects, are not associated or affiliated with IEEE, in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, and not projects of or by IEEE.
