Literature review for topic Machine Learning for Credit Card Fraud Detection
Budget: €30 – €250 EUR
I am seeking an academic expert with deep understanding of machine learning algorithms, specifically decision trees, neural networks and support vector machines. The task is to carry out an extensive literature review on their application in detecting credit card fraud.
In particular, the service provider needs to:
• Compare the mentioned algorithms based on published research papers.
• Evaluate each algorithm's accuracy, precision and recall, and computational efficiency. This will help determine the most effective continuous learning approach.
Given that I am in urgent need of this task's completion, I require someone ready to dedicate a significant portion of their time to the project.
Ideal candidates should have:
• Proven experience in machine learning.
• Excellent research and academic writing skills.
• Familiarity or experience in the finance sector would be a plus but it is not mandatory.
Please provide evidence of past similar projects when placing your bid. Application deadline is strict due to the urgency of the task. If you can't commit to the deadline, do not bid. Looking forward to insightful submissions. Thank you.
In particular, the service provider needs to:
• Compare the mentioned algorithms based on published research papers.
• Evaluate each algorithm's accuracy, precision and recall, and computational efficiency. This will help determine the most effective continuous learning approach.
Given that I am in urgent need of this task's completion, I require someone ready to dedicate a significant portion of their time to the project.
Ideal candidates should have:
• Proven experience in machine learning.
• Excellent research and academic writing skills.
• Familiarity or experience in the finance sector would be a plus but it is not mandatory.
Please provide evidence of past similar projects when placing your bid. Application deadline is strict due to the urgency of the task. If you can't commit to the deadline, do not bid. Looking forward to insightful submissions. Thank you.