Nanavath Swapna
Professional Summary
Machine Learning Engineer with 0 years of experience building ML and computer vision models, data preprocessing pipelines, and data visualizations through internships and academic projects. Hands-on with Python, NumPy, Pandas, scikit-learn, TensorFlow, PyTorch, OpenCV, and REST API development using Django. Completed internships in Python development and data visualization; led major undergraduate projects including a Parkinson's disease detection model and an AI-based internship recommendation engine.
Technical Skills
Work Experience
- Developed reusable Python scripts to automate data extraction and preprocessing workflows using Pandas and NumPy, reducing manual steps in class assignments and project work.
- Built command-line utilities and modular functions for CSV/JSON parsing and transformation to standard formats used by downstream ML models.
- Implemented unit tests and basic input validation for core modules to improve script reliability during iterative development.
- Collaborated via Git and GitHub: managed branches, submitted pull requests, and resolved merge conflicts to maintain a clean codebase.
- Optimized data-loading routines to reduce memory footprint by using chunking and dtype specification when processing large CSVs.
- Documented code usage and created short README guides to accelerate handover and enable reuse across subsequent academic projects.
- Cleaned and preprocessed heterogeneous datasets with Pandas to prepare time-series and categorical data for visualization.
- Designed and implemented visualizations using Matplotlib and Seaborn to highlight trends, anomalies, and key KPIs for stakeholder-style reports.
- Constructed reproducible Jupyter Notebook workflows combining data cleaning, exploratory analysis, and final charts for presentation.
- Translated visual analysis into concise written insights and recommendations to inform simple data-driven decisions.
- Version-controlled notebooks and visualization assets with GitHub, maintaining clear commit history and descriptive messages.
- Presented findings through a short slide deck linking visual outputs to actionable conclusions for a non-technical audience.
- Performed a comprehensive IAM assessment exercise, identifying role-based access gaps and over-privileged accounts in the simulated environment.
- Designed an IAM solution using RBAC principles to align permissions with least-privilege practices and business-role requirements.
- Specified multi-factor authentication (MFA) and single sign-on (SSO) configurations to strengthen account security and simplify user access flows.
- Prepared implementation documentation and a stepwise rollout plan describing required configuration, testing, and verification steps.
- Mapped security controls to common best practices and documented rationale for recommended changes to support stakeholder review.
- Summarized technical findings and recommendations in a structured report suitable for handover to engineering and operations teams.
Projects
- Implemented a prototype image search interface using HTML and JavaScript to accept user queries and display ranked image results.
- Processed and indexed images using Python and OpenCV for feature extraction, enabling visual similarity-based retrieval.
- Built a classification pipeline using clinical/voice features to detect Parkinson's disease, including feature selection and model evaluation.
- Evaluated multiple supervised models with cross-validation and reported performance metrics to select the best-performing approach for the dataset.
- Designed and implemented a recommendation engine to match student profiles to internship listings using feature engineering and similarity scoring.
- Exposed recommendations through a simple Django-based API allowing programmatic retrieval of ranked internship suggestions.
- Completed hands-on tasks assessing identity and access management; designed role-based access controls and MFA/SSO strategies.
- Produced implementation documentation demonstrating pragmatic rollout steps and validation checks for recommended controls.
Education
Certifications
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