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Brahmani GajagouniBG
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Brahmani Gajagouni

@brahmanigajagouni

AI/ML engineering graduate who developed machine learning models and a deepfake audio detector using Python, Scikit-learn, and TensorFlow.

India
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What I'm looking for

I'm interested in building LLM-powered applications, agentic workflows, RAG systems, and intelligent automation solutions.

For my Liver Disease Prediction Using Machine Learning project, I developed predictive models with Logistic Regression, SVM, and Random Forest. I applied preprocessing, feature selection, and GridSearchCV to optimize the models.

I built deep learning models for Deepfake Audio Detection using MFCC and spectrogram features, gaining experience with audio processing workflows.

During virtual internships at CodSoft and Bharat Intern, I worked on data preprocessing, exploratory data analysis, and machine learning models using Python and Scikit-learn. I'm interested in building LLM-powered applications, agentic workflows, RAG systems, and intelligent automation solutions.

Experience

Work history, roles, and key accomplishments

BI

Machine Learning Intern

Bharat Intern

Jan 2024 - Feb 2024 (1 month)

Completed a 1-month virtual internship in Machine Learning, developing models using Python and Scikit-learn, and performing data preprocessing, model training, and evaluation on real-world datasets.

Education

Degrees, certifications, and relevant coursework

JE

Jayaprakash Narayana College of Engineering

B.Tech, Artificial Intelligence & Machine Learning

2022 -

Grade: 7.90/10

Pursuing a B.Tech in Artificial Intelligence & Machine Learning with a CGPA of 7.90/10, expected to graduate in May 2026.

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