https://github.com/recker-dev/resume

A concise, resume showcasing my projects, technical skills, and academic background. Regularly updated to reflect new work, internships, and achievements.
https://github.com/recker-dev/resume

Last synced: 4 months ago
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A concise, resume showcasing my projects, technical skills, and academic background. Regularly updated to reflect new work, internships, and achievements.

• Host: GitHub
• URL: https://github.com/recker-dev/resume
• Owner: Recker-Dev
• Created: 2025-04-10T07:38:17.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-06-13T12:54:34.000Z (about 1 year ago)
• Last Synced: 2025-09-01T20:49:59.728Z (9 months ago)
• Size: 338 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Swapnendu Banik

**Location:** Kolkata, India  

**Email:** [reckerdev@gmail.com](mailto:reckerdev@gmail.com)  

**GitHub:** [Recker-Dev](https://github.com/Recker-Dev)  

**LinkedIn:** [LinkedIn](https://www.linkedin.com/feed/)

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## Summary

Detail-oriented and innovative computer science undergraduate passionate about AI, IoT, and NLP. Experienced in developing and deploying machine learning pipelines with hands-on expertise in data streaming, computer vision, and natural language processing.

---

## Education

- **VIT Bhopal University, B.Tech in CSE with specialization in Health Informatics**  

  *CGPA:* 8.67

- **Delhi Public School, Ruby Park, Class 12 (CBSE)**  

  *Score:* 86%

- **Calcutta Public School, Kalikapur, Class 10 (ICSE)**  

  *Score:* 94%

---

## Experience

**Machine Learning Intern – PreProdCorp**  

*Jan 2024 – Feb 2024*  

Offered placement after securing 4th place in Buildathon 2024. Worked on agile-based ML pipelines involving Apache Kafka, Linux/WSL, and PySpark for data preprocessing. Built tree-based models and a Deep Q-Network for CartPole using reinforcement learning. Contributed to full-stack workflows with MLFlow, DVC, and Dagshub, and explored NLP using Hugging Face (DistilBERT, RoBERTa, GPT-2, T5). Also led sentiment analysis on Amazon Reviews with TF-IDF, Word2Vec, and fine-tuned models.  

**Codebases:** [Internship Work](https://github.com/Recker-Dev/PreProd-Internship-Work) | [Exploring NLP](https://github.com/Recker-Dev/Exploring-NLP)

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## Skills

- **Hardware:** IoT, Raspberry Pi  

- **Languages:** Python, SQL, Java, C++  

- **Frameworks:** Pandas, Scikit-Learn, PyTorch, Matplotlib, LangGraph, LangChain  

- **Soft Skills:** Project Management, Problem Solving

---

## Projects

- **GenAI Based Mini-CDSS:**  

  Developed a Streamlit application to assist doctors during initial patient encounters by generating preliminary reports and diagnoses, enhancing clinical decision-making.  

  [GitHub](https://github.com/Recker-Dev/Mini-CDSS-Streamlit-Frontend)

- **IoT-based Network Attack Predictor:**  

  Created a machine learning tool to detect cyberattacks in IoT healthcare networks using PCA for dimensionality reduction and an ANN for classification. Coupled with a FastAPI backend and Streamlit UI for real-time inference.  

  [GitHub](https://github.com/Recker-Dev/IOT-Healthcare-Network-Traffic-Attack-Predictor)

- **Alzheimer Detection:**  

  Implemented a TinyVGG16-based CNN to classify MRI scans into stages of Alzheimer's Disease (No Impairment, Very Mild, Mild, Moderate Impairment) and built a Streamlit app for user-friendly inference.  

  [GitHub](https://github.com/Recker-Dev/alzheimer-cnn-tinyVGG16)

- **Sign Language Detection Prototype:**  

  Developed a prototype to recognize sign language gestures using machine learning, currently under re-evaluation for performance improvements.  

  [GitHub](https://github.com/Recker-Dev/Project-Sanket-Sign-Language-Detection-Prototype)

- **Upcoming Project – IoT-based Dynamic Attendance Management System:**  

  Designing a system that manages attendance dynamically based on time slots, leveraging IoT technologies for enhanced accuracy and efficiency.

---

## Achievements

- **4th Place** in Buildathon 2024 at VIT Bhopal (offered placement with PreProdCorp)

- **6th Place** among 500+ teams in a Johns Hopkins University HealthHack organised in association with VIT Bhopal