Credit Card Fraud Detection
Summary
Build an explainable fraud detection system to identify credit card fraud while maintaining transparency
Work
Qwipo
|Machine Learning Intern
Summary
Develop and integrate image processing solutions and APIs to improve system efficiency and experience
Highlights
Integrated image processing into a Flask using OpenCV for background removal and PIL for resizing with endpoints
Developed a model for SKU similarity using cosine similarity and TF-IDF on 50k SKUs, achieving 93% accuracy
Developed an API for ONDC application using BecknProtocol, ensuring integration with Node.js and Express
Optimized CockroachDB SQL queries and integrated HTML/TypeScript for improved data retrieval efficiency
Key Skills: OpenCV, PIL, Flask, Node.js, Express, CockroachDB SQL, HTML, TypeScript, TF-IDF
Education
Indian Institute of Technology, Kharagpur
Btech
Civil Engineering, Micro Specialization - Artificial Intelligence
Grade: 7.72 CGPA
Awards
Selected for AmazonML Summer School
a program focused on machine learning topics led by Amazon scientists
Earned Oracle Cloud Infrastructure 2024 Generative AI Professional certification (85%)
showcasing expertise in LLM architecture, OCI Generative AI Services, and AI application development with RAG and LangChain
Skills
Languages
C, C++, Python, MySQL, Matlab.
Fundamentals
DSA, Image Processing, Statistics, ML, DL, NLP, GenAI.
Libraries
OpenCV, NLTK, PyTorch, Sklearn, Pandas, Transformers, Seaborn, Matplotlib, NumPy.
Models
Linear Regression, CNN, VGG19, RNN, LSTM, GRU, BERT, Gradient Boosting, LLama2.
Big Data Technologies
FAISS, ChromaDB.
Tools
PyCharm, Docker, Kubernetes, Google Colab, Jupyter.
Projects
SQL Query Retrieval
Summary
Enhance accessibility by converting SQL queries into natural language responses for improved interaction
Sentiment Analysis
Summary
Build a sentiment analysis model using a fine-tuned BERT to classify sentiment in Twitter data