ABOUT ME
I'm a computer science engineering student at
INSAT
university, specializing in AI and passionate about its quick progress.
š§āš» ML & MLOps Enthusiast
š Google Cloud Professional ML Engineer
Certified.
š¤ Focused on LLMs and Generative AI.
āļø Experienced in Google Cloud Platform (GCP).
WHAT I OFFER
As a machine learning engineer, I design and build intelligent systems that can analyse data, learn from it, and make predictions. I offer expertise in developing and deploying AI models that help businesses automate processes and optimize operations.
SKILLS
With a knack for quick learning, I focus on mastering many skills and technologies needed for Machine Learning.
EXPERIENCE
I have over 3 years of experience working on many projects and technologies.
Here is a timeline of my key experiences.
- Built an NL2SQL system that converts prompts from sales managers into SQL queries and generates natural language responses about customers billing information.
- Worked with Gemini LLM and achieved approximately 95% output accuracy.
- Performed SQL query optimization, improving information retrieval speed and enhanced LLM output accuracy through well-structured prompt engineering.
- Deployed the application using Google Cloud Run and managed a CI/CD pipeline with Google Cloud Build
- Developed a chatbot using the pre-trained Llama 2 model with 7 billion parameters to deliver detailed information about the company's services to clients.
- Employed Retrieval-Augmented Generation (RAG) techniques to optimize LLM text generation, resulting in an improvement of approximately 30% in output quality.
- Implemented a solution for colon disease detection that reduces 72% of false positives.
- Enhanced diagnostic precision in colon disease detection through advanced data augmentation and EfficientNet model optimization techniques.
Personal Project
- Developed an autonomous robot navigation system employing the TD3 algorithm, resulting in a significant 85% improvement in navigation accuracy.
- Implemented deep reinforcement learning techniques to enable obstacle avoidance, achieving a 92% success rate in various test environments.
Personal Project
- Built an information retrieval system about soccer based on 1000+ PDF file pages.
- Applied Llama 2 Model and RAG techniques, achieving an exceptional 95% accuracy in information retrieval.
- Utilized the Streamlit library to develop and showcase an interactive web app