Rakesh Laggala
Professional Summary
AI/ML Engineer with 0 years of experience building NLP models and integrating them into full‑stack web prototypes. Experienced in Python, Scikit‑learn, Pandas and NumPy for text preprocessing, TF‑IDF vectorization and model evaluation; developed a Fake News Detection model using PassiveAggressiveClassifier that achieved 96% test accuracy during an internship. Integrated ML services with React frontends and Node.js backends and implemented Firebase persistence for user feedback and logs. Built multiple web and platform projects using TypeScript, React, Tailwind CSS, RESTful APIs, Google Cloud, PHP and MySQL to support deployment‑ready prototypes. Comfortable automating data flows with Git workflows and producing documentation for handoff. Seeking an entry‑level AI/ML engineering role to apply NLP expertise and hands‑on full‑stack integration skills to productionize ML solutions.
Technical Skills
Work Experience
- Designed and trained a text‑classification pipeline using Scikit‑learn's PassiveAggressiveClassifier and TF‑IDF features, achieving 96% accuracy on the held‑out test set.
- Preprocessed and vectorized large text corpora using Python with Pandas and NumPy; implemented data cleaning, tokenization and TF‑IDF feature pipelines to improve model precision.
- Built a React frontend component for real‑time prediction UI and integrated it with a Node.js backend API to handle inference requests and validation.
- Implemented Firebase persistence to capture user feedback and prediction logs to enable iterative retraining and auditing of model outputs.
- Automated data flow and scheduled report generation between model artifacts and the web interface using Python scripts and Git workflows for reproducible runs.
- Evaluated model quality with cross‑validation and classification metrics and packaged deployment‑ready model artifacts and documentation for handoff to the product team.
Education
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