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Parbin Pradhan1

Parbin Pradhan is an AI and ML expert with experience in Python and C, currently pursuing a B.Tech in Computer Science at NIST University. He has completed a vocational training project on a face recognition attendance system and has worked on projects like credit card fraud detection and nitrogen percentage prediction. Parbin is proficient in multiple programming languages and has certifications in advanced C programming and data structures.

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0% found this document useful (0 votes)
6 views3 pages

Parbin Pradhan1

Parbin Pradhan is an AI and ML expert with experience in Python and C, currently pursuing a B.Tech in Computer Science at NIST University. He has completed a vocational training project on a face recognition attendance system and has worked on projects like credit card fraud detection and nitrogen percentage prediction. Parbin is proficient in multiple programming languages and has certifications in advanced C programming and data structures.

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ashutoshsabat17
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PARBIN PRADHAN

Berhampur, Ganjam, Odisha, India,


760001
parbinpradhan538@gmail.com
7064050999
https://www.linkedin.com/in/parbin-pradhan-a07a02274?
utm_source=share&utm_campaign=share_via&utm_content=profile&utm_medium=an
droid_app

SUMMARY:
Experienced in AI and ML with proficiency in Python and C language, adept at
developing and deploying machine learning models for various applications,
emphasizing problem- solving skills and data analysis expertise.

EDUCATION :
Bachelors of Technology(Computer Science and Engineering)
NIST University, Dec 2021 - Present
Berhampur CGPA -
6.7/10.00
Intermediate May 2019 - Jun
Aaryan Gurukul higher secondary school , Berhampur 2021
Percentage - 68
Matriculation
Saraswati shishu bidya mandir, Mar -2019
ramaharinagar Percentage- 67

EXPERIENCE:
Vocational Trainee (CTTC)
Creating project on face recognition attendance
system June 2023-july
2023
SKILLS:

C
Programming
Python
Data Science and
Algorihtms AI & Machine
Learning
Java

PROJECTS:
Credit card Fraud detection
Credit card fraud detection with machine learning involves training
algorithms on past transaction data to recognize unusual patterns that may
indicate fraudulent activity. By analyzing factors like transaction amounts,
locations, and frequencies, these algorithms can identify potential fraud and
alert financial institutions to take action, safeguarding cardholders from
unauthorized charges and minimizing financial losses.
Nitrogen percentage prediction
Nitrogen percentage prediction involves using machine learning algorithms to
analyze soil data and forecast the nitrogen content present, aiding in
agricultural decision-making processes and optimizing crop yield and quality.
LANGUAGE:

English
Hindi
Odia
CERTIFICATION:
Advanced C Programming and Data Structures
Face recognition attendance system using AIML
DECLARATION:
I hereby declare that all the information provided in this resume is true and
accurate to the best of my knowledge.

Signature

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