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Aruna Dugganapalli

@arunadugganapalli

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Machine Learning Intern at Slash Mark who built a facial emotion recognition system with 93% accuracy.

India

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What I'm looking for

I'm seeking an entry-level software development role where I can apply my problem-solving skills and technical foundation to build and contribute to real-world applications.

At Slash Mark, I applied machine learning concepts to build and evaluate predictive models on real-world datasets, using Python-based libraries for preprocessing, feature engineering, and model evaluation.

For my facial emotion recognition project, I designed and implemented a CNN-based system for static images and live video, integrating its outputs with an automated music therapy recommendation module. It achieved 93% accuracy in real-time classification.

I also developed a house price prediction project using regression models, Pandas, NumPy, and Scikit-learn. I'm seeking an entry-level software development role where I can apply my technical foundation to build and contribute to real-world applications.

Experience

Work history, roles, and key accomplishments

Machine Learning Intern

Slash Mark

Jul 2025 - Sep 2025 (2 months)

Applied machine learning concepts to build and evaluate predictive models on real-world datasets. Carried out data preprocessing, feature engineering, and model evaluation using Python-based ML libraries.

Machine Learning data preprocessing Feature Engineering Model Evaluation Python

Python Programming Intern

Motion Cut

Jul 2024 - Aug 2024 (1 month)

Developed and debugged Python scripts and small applications, reinforcing core programming and problem-solving skills. Practiced data structures, file handling, and object-oriented programming concepts through guided exercises.

Python Debugging Data Structures File Handling Object Oriented Programming