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Hi, I am Sneh Shah.

Aspiring Data Scientist

I am a highly motivated individual living in Bangalore, completing my Masters in Data Science from Christ University. With a competitive nature, I passionately solve problems and build things, showcasing excellent problem-solving skills and a proven ability to adapt quickly to new environments and technologies.


Mail: snehshah2901@gmail.com

Contact: +91 9428911398


Resume

Projects

Neural Style Transfer

Orchestrated the research and development of a Neural Style Transfer project, analyzing recent advances and 2 main techniques. Engineered a high-performance NST system with approximately 30% reduction in processing time using L-BFGS optimization.

  • Python
  • Pytorch
  • Deep Learning
  • Artistic Image Enhancement
  • L-BFGS optimization

Diabetic-Retinopathy Detection

This project aims to use Diabetic retinopathy detection using features from deep learning and fitting into machine learning algorithms and the data is taken form the kaggle.

  • Python
  • Tensorflow
  • OpenCV
  • Scikit-Learn
  • Pandas

CreditCard Fraud Detection

This project is focused on building a credit card fraud detection system using a dataset from Kaggle. The goal is to develop a machine learning model that can accurately detect fraudulent credit card transactions and minimize false positives.

  • Python
  • Keras
  • Scikit-Learn
  • Machine Learning
  • Matplotlib

Internships & Certifications

Saleken (ML Intern)

• Optimized the Whisper-ASR codebase through Docker deployment, documenting streamlined steps. • Elevated code quality by introducing 2 specialized modules for speaker diarization and voice activity detection. • Successfully deployed Emotion Detection models on Triton Inference Server, optimizing configurations and integrating metrics with Prometheus for effective monitoring.

  • Python
  • Docker
  • Triton Inference Server
  • LLMs
  • Fastapi
  • Hugging Face
  • VAD

Open Weaver

• Developed a customized interface for Chat-GPT, acquiring hands-on experience in seamlessly integrating AI language models.• Utilized Open AI's Whisper and DALL-E tools to convert audio into visually generated images.• Applied deep learning algorithms and computer vision methods to detect and mark Deep-Fake images.

  • Python
  • Gen -AI
  • NLP
  • Deep Learning
  • gradio
  • NLTK
  • Spacy

Skills

Languages

  • Python
  • SQL
  • R
  • Matlab
  • Java

Tools and Frameworks

  • Git
  • Tableau
  • PowerBI
  • Weka
  • MS Excel
  • AWS

Libraries

  • Scikit-Learn
  • NumPy
  • Pandas
  • OpenCV
  • TensorFlow
  • Keras
  • Pytorch
  • Matplotlib
  • Seaborn
  • Transformers
  • Spacy
  • NLTK