Presentation on Data science internship, credit card transaction fraud detection and analysis

This is my internship presentation on fundamentals of data science

1. Internship : Data Science 1 Presented by - Sushmita Annigeri

2. 2 Student Name SUSHMITA ANNIGERI University RDPR UNIVERSITY Branch M.Sc Computer Science(Data Analytics) USN / Reg No: 2201502010 Internship Duration 4 Weeks ( 20 th November 2023 to 20 th December 2023 ) Company Internship Guide Mr. Amitkumar S , Application Developer InfiData Technologies

3. Contents 3 About InfiData Technologies Internship Tasks Introduction on Final Project Software / Hardware Tools Details Implementation Details Skills Utilized What I Learnt ? Internship Outcomes Project Demo / Screenshots Conclusion

4. Internship Tasks 4 4 Task on: Looping Statement Problems Conditional Statement Machine Learning Libraries: Numpy , Pandas, Seaborn and Matplotlib Machine learning Algorithm and working with dataset Project Work

5. Introduction to Project: Project Name : Credit Card Fraud Detection and Visualization introduction: This is thee credit card transaction that contains legitimate and fraud transaction. From the duration 1 st January 2019 to 31 st December 2020. Location: USA It covers the credit card transaction with 1000 customers. Doing the transaction with 800 merchants. 5

6. 6 Dataset colmns

7. 7 Dataset

8. Skills Utilized 8 Python programming Machine Learning Algorithms

9. What I learn t ? 9 Technical skills: Python ML Algorithms Working with Libraries and datasets Soft skills: Teamwork Communication S kills Management skills : P roject M anagement , T ime M anagement

10. Internship Outcomes 10 Proficiency on performing the libraries Basic Statistics Working with supervised and unsupervised machine learning algorithms Growth : Critical Thinking and analysis Working with projects

11. Project Demo / Screenshots Displaying Gender

12. 12 Gender vs Fraud

13. 13 Spending Category vs Fraud

14. 14 Age vs Fraud

15. 15 Cyclicity of credit card fraud -Hourly trend

16. 16 Weekly trend

17. 17 Monthly Trend

18. 18 State vs frauds:

19. 19 Transaction amt vs fraud

20. Thank You 20