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High on Machine Learning
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High on Machine Learning

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Chandra Prakash Bathula

📍 Saint Louis, MO   |  ✉️ chandraprakash.bathula@slu.edu | 🔗 LinkedIn  |  GitHub  |  Medium  |  Portfolio


🎓 Education

Master of Computer & Information Sciences
Saint Louis University, MO • Aug 2022 – May 2024
GPA: 3.93 / 4.00


🛠 Technical Skills

Python R SQL MATLAB JavaScript TypeScript Tableau Power BI Excel Pandas NumPy Matplotlib Seaborn scikit-learn TensorFlow PyTorch Keras GitLab GitHub VS Code PyCharm Jupyter AWS Flask Django React Vue.js Node.js Express Jira Agile API Data Pipelines

💼 Professional Experience

Machine Learning Engineer • EliteNotes

Jun 2023 – Present

  • Developed a Python-based transcription system achieving 95% accuracy, integrated multilingual translation with 98% accuracy, processing 10,000+ files/day using React.js & Node.js
  • Optimized data‑preprocessing pipeline, halving processing time and improving real‑time transcription/video‑to‑text conversion by 50%

UX Research & ITS Workflow Analyst • Saint Louis University

Mar 2023 – Dec 2023

  • Built web interfaces for lost‑and‑found management & 3D‑printing ticketing, boosting efficiency by 40% and user engagement by 25%
  • Analyzed end‑user data for TeamDynamix iPaaS; automated workflows to cut workload by 15% and improve response times by 30%

Associate Software Engineer • Qentelli Solutions Pvt Ltd

Mar 2021 – Jul 2022

  • Collaborated on recommendation algorithms using user feedback, increasing engagement metrics
  • Developed UI components with React.js/Vue.js; implemented cosine similarity & Manhattan distance methods to achieve 90% customer sentiment prediction accuracy

📁 Project Experience

VizFlixGPT

JavaScript • React.js • Redux • Firebase • TMDB API • OpenAI GPT
Built AI-driven movie recommendation platform serving 1,000+ users; increased session duration by 25%.

TubeFlix

JavaScript • React.js • Tailwind CSS • YouTube API • Firebase
Developed a responsive video‑streaming app with dynamic search & smart recommendations, improving engagement by 25%. Try here

EliteNotes App

JavaScript • LLM • TF‑IDF • Word2Vec • React.js • Firebase Auth
Engineered end‑to‑end ML‑powered transcription & summarization features, processing 10,000+ files/day with 50% efficiency gain. Try here

Apparel Recommendation System

Python • BoW • TF‑IDF • Word2Vec • VCG‑CNN
Processed 180K+ images; boosted recommendation accuracy by 20% using hybrid NLP and computer‑vision techniques.

New York Taxi Demand Prediction

Python • Linear Regression • Random Forest • XGBoost
Achieved <12% MAPE on taxi demand forecasting using time‑series analysis, clustering, and ensemble methods.

Tableau Dashboards

Tableau
Designed 3 interactive dashboards (salary data, Netflix catalog, Amazon sales) showcasing advanced visual analytics. Try here

Farmers App (Figma Prototype)

Figma
Designed an end‑to‑end farmers’ marketplace for climate data, supply‑chain, and crop sales, reducing manual effort by 40%. Try here


🏆 Awards & Achievements

  • 🎓 Distinguished Student Award for master’s research (GPA 3.93/4.00)
  • 🖋 Authored 100+ technical articles on Medium & LinkedIn

⭐️ “Every day brings new data, new insights, and new possibilities.” ⭐️

Pinned Loading

  1. Apparel-Recommendations Apparel-Recommendations Public

    This project implements a personalized apparel recommendation engine using content-based search with the Amazon API, NLTK, and Keras libraries.

    Jupyter Notebook 17

  2. LLM_Finance_Project LLM_Finance_Project Public

    Jupyter Notebook 2

  3. LLM_Project LLM_Project Public

    Jupyter Notebook 2

  4. Movie-Recommendation-System Movie-Recommendation-System Public

    A Comparative Machine Learning Case Study: Movie Recommendation System Using Collaborative Filtering and Content-Based Filtering

    Jupyter Notebook 2

  5. PCA-in-3D PCA-in-3D Public

    3D visualizations of vector embeddings.

    Jupyter Notebook 2 1

  6. TV-SHOW-RECOMMENDATIONS TV-SHOW-RECOMMENDATIONS Public

    TV Shows recommendation system using cosine-similarity in ML with the help of TMDB dataset 🍿🎬.

    Jupyter Notebook 2