Urvi Tyagi

About

Final-year B.Tech student specializing in Artificial Intelligence & Machine Learning with hands-on experience in machine learning, NLP, generative AI, and data analytics. Builds Python-based AI applications and scalable ML solutions using tools like TensorFlow, Scikit-learn, Streamlit, Docker, and Supabase.

Experience

• Machine Learning Intern
  InAmigos Foundation (IAF)
  Aug 2026 – 2026

  Exploring the fundamental concepts of Artificial Intelligence and Machine Learning as part of a structured learning internship. • Studying Artificial Intelligence, Machine Learning, Deep Learning, Supervised Learning, Unsupervised Learning, and Reinforcement Learning. • Understanding each concept through simple explanations and real-world examples. • Preparing a structured learning guide to document key concepts and learnings. • Developing foundational understanding of how AI and Machine Learning work.

• Artificial Intelligence Intern
  IBM SkillsBuild
  Jun 2026 – Aug 2026

  Completed a virtual internship focused on Artificial Intelligence through IBMmooc. Developed practical understanding of AI concepts, tools, and applications. Applied AI/ML concepts through hands-on learning and internship activities. Strengthened foundational skills in Artificial Intelligence, Machine Learning, and Generative AI.

• GenAI & Data Analytics Project Trainee
  Tata iQ
  Aug 2025 – —

  • Conducted exploratory data analysis using Generative AI tools to identify customer behavior patterns and delinquency risks. • Developed predictive approaches for risk segmentation and collections prioritization. • Applied Responsible AI principles, including fairness, transparency, and Explainable AI (XAI), in solution design. • Gained practical exposure to AI-driven business analytics and data-informed decision making.

Education

• Bachelor of Technology (B.Tech)
  Dr. A.P.J. Abdul Kalam Technical University
  Artificial Intelligence & Machine Learning · 2027

Skills

• SQL
• C
• Computer Vision
• Python
• Software Testing
• Feature Engineering
• Model Evaluation
• NumPy
• Pandas
• Streamlit
• scikit-learn
• PyTorch
• TensorFlow
• Keras
• API Integration Understanding
• Natural Language Processing
• XGBoost
• Transfer Learning
• Oop
• Generative AI (ChatGPT, Copilot, Gemini)

Projects

• Multimodal Product Price Prediction
  Python, TensorFlow, XGBoost

  An end-to-end multimodal machine learning pipeline combining textual and visual product information for price prediction. Implemented TF-IDF feature extraction, EfficientNet image embeddings, feature engineering, and XGBoost regression. Evaluated model performance using MAE, RMSE, and R2 while comparing multiple feature extraction and regression approaches.

• TalentLens AI
  Python, NLP, Streamlit

  An intelligent resume screening platform that ranks candidates against job descriptions using TF-IDF, Sentence Transformers, and cosine similarity. Implemented semantic search, recruiter dashboards, and skill-gap analysis to support candidate evaluation workflows. Built an interactive application for resume parsing, candidate ranking, and personalized learning recommendations.

• ML Copilot Platform
  Python, Streamlit, Docker, Supabase

  A modular platform to simplify the machine learning lifecycle through dataset management, experiment tracking, and workflow automation. Designed reusable backend modules and AI-assisted utilities for project organization, feature engineering, model evaluation, and experiment management. Integrated Docker, REST APIs, and Supabase for authentication, backend services, and portable deployments.

Courses & certifications

• Practicing Test Driven Development with Python
• Introduction to Generative AI · AWS
• Prompt Design in Vertex AI · Google Cloud
• Build Your Own Small Language Model · Google DeepMind
• Google Cloud Gemini for Data Scientists and Analysts · Google Cloud
• IBM Machine Learning with Python · IBM