Machine Learning Data Science

PAVITHRA B

Email: *************@*****.*** Mobile: 962-***-****

ABOUT ME

Aspiring Data Scientist passionate about solving real-world problems using AI, Data Science, and Machine Learning. Proficient in Python and Data Analytics with a strong ability to extract meaningful insights. Skilled in Software Development and Testing, capable of building and validating reliable applications. Eager to create impactful, data-driven solutions across diverse domains. EDUCATION

Bachelor of Technology Artificial Intelligence and Data Science CGPA-7.81 Rathinam Technical Campus,TN 2021-2025

Higher Secondary Certificate 87%

C.S.I Girls Higher Secondary School 2020-2021

TN State board, Tiruppur.

Secondary School Leaving Certificate 79%

Government High School 2018-2019

TN State board, Tiruppur.

SKILLS SUMMARY

Technical Skills: Python, SQL, Power BI, Machine Learning

Soft Skills: Problem Solving, Leadership skills, Team Working skills, Good Communication skills, Decision Making

Languages: Tamil, English

INTERNSHIP

CodeSoft:Data Science

Data Analysis & Machine Learning: Collected, cleaned, and analyzed large datasets to identify key patterns. Built predictive models using Python and Scikit-learn to support data-driven solutions and improve decision-making.

Data Visualization: Designed impactful visualizations using Power BI and Matplotlib to present insights clearly, helping stakeholders make informed and strategic decisions. PROJECTS

Credict Card Fraud Deduction using ML

● Developed a Machine Learning model to detect fraudulent credit card transactions by analyzing transactional patterns such as amount, time, and location. Leveraged historical transaction data to train the model in identifying anomalies that indicate potential fraud.

● Performed data preprocessing, feature selection, model training, and evaluation using tools like Python, Pandas, and Scikit-learn. Cleaned and normalized data, selected key features influencing fraud, and trained models like Logistic Regression and Random Forest.

● Technology Stack-Python, Pandas, NumPy (Data preprocessing), Scikit-learn (ML algorithms), Matplotlib, Seaborn (Data visualization), Jupyter Notebook, Logistic Regression, Decision Tree, Random Forest (Models). WEB PRESENCE

LINKEDIN- www.linkedin.com/in/pavithrajee

GITHUB- https://github.com/Pavi-b

CERTIFICATES

Coursera (IBM University) – Data Analyst Certification

Coursera – Python for Data Science

NASSCOM – Introduction to Cyber Security

CISCO – Certified in Introduction to IoT

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