
Brahmani Gajagouni
@brahmanigajagouni
AI/ML engineering graduate who developed machine learning models and a deepfake audio detector using Python, Scikit-learn, and TensorFlow.
What I'm looking for
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
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.
Data Science Intern
CodSoft
Nov 2023 - Dec 2023 (1 month)
Completed a 4-week virtual internship in Data Science, working on data preprocessing, exploratory data analysis, and machine learning concepts using Python.
Education
Degrees, certifications, and relevant coursework
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.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Salary expectations
Job categories
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