Shrey Mishra

Pursuing a Bachelor's degree in Computer Science, expected 2027.

Specializing into the depths of Machine Learning

Experience

• Artificial Intelligence Intern | BetaZen InfoTech, Remote
  Feb. 2026 - Apr. 2026

  Developed an automated system to generate questions and answers using reference PDF files for Classes 5-8, covering all textbooks and lessons under the West Bengal Bengali Board curriculum.

Projects

• House Prices Prediction-Kaggle Notebook

  Built a machine learning model to predict housing prices using regression techniques and feature engineering. Submitted as a Kaggle notebook for the House Prices: Advanced Regression Techniques competition. Focused on data cleaning, analysis, and model evaluation to improve prediction accuracy.

• Personalized Recommender System with Unsupervised User Segmentation-Kaggle Notebook

  This project is an end-to-end data pipeline that combines unsupervised learning and recommendation algorithms to analyze user behavior and provide personalized content suggestions using the MovieLens-100K dataset.

• RPS Classifier (CNN + Transfer Learning)-Kaggle Notebook

  Built an image classification model to recognize rock, paper, and scissors hand gestures using a baseline CNN and MobileNetV2 transfer learning with fine-tuning, achieving ~99%+ validation accuracy.

• IMDB Sentiment Analysis (Baseline vs LSTM vs GRU)-Kaggle Notebook

  Built an NLP sentiment classifier on IMDB reviews using embeddings and sequence models (LSTM, GRU), and compared them using accuracy/loss trends and confusion matrices.

• DocuRAG

  Built a containerized document Q&A system using Retrieval Augmented Generation (RAG) with FastAPI, Google Gemini API, and ChromaDB, enabling users to upload documents and receive AI-powered answers with streaming responses; fully deployed with Docker Compose for seamless scalability.

• HireBot

  Developed an AI-powered hiring assistant using LLaMA 3.3 via Groq API with Streamlit frontend, implementing structured 5-stage interview pipelines and dynamic prompt engineering for context-aware technical Q&A generation. Integrated DistilBERT sentiment analysis with real-time candidate profiling, session analytics, and GDPR-compliant data export.