A Journey in Cloud and DevOps

As an AWS Certified DevOps Engineer with a Master's degree in Artificial Intelligence and 5 years of experience, I specialize in bridging the gap between cloud engineering and AI. My expertise spans Red Hat environments, AWS, and a suite of DevOps tools including Docker, Jenkins, Kubernetes, and Ansible. This section details my professional journey, underlining my commitment to innovation and excellence in cloud and DevOps domains.

Mastery in AI Technologies

My fascination with AI is reflected in my proficiency with tools like TensorFlow, PyTorch, MLflow, and Kubeflow. Having completed numerous projects using these technologies, I have gained a deep understanding of how to leverage AI to solve real-world problems. This section showcases my AI-centric projects and contributions to the field, particularly focusing on LLM and RAG architectures, generative AI, and my work with the HuggingFace platform.

Leading the Way in LLM and Generative AI

My passion for Large Language Models (LLM) and Generative AI is the cornerstone of my recent work. Utilizing OpenAI's API and Llama LLM, I have developed innovative projects that push the boundaries of what's possible in natural language processing and understanding. This section explores my groundbreaking work in this area, highlighting how I leverage these advanced technologies to create novel solutions.

Some of My Projects

Here's a selection of my projects that reflect my expertise in cloud and AI technologies. Each project represents a unique challenge and showcases my innovative approach to problem-solving.

YouTube Made Easy Project

YouTube Made Easy

A project focused on simplifying the YouTube experience, leveraging advanced APIs and user-friendly interfaces.

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Pet Name Generator Project

Pet Name Generator

An innovative and fun project that uses AI to generate unique and creative names for pets.

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Vector Search Chatbot Project

Vector Search Chatbot

Enhancing chatbot performance using vector search, a project that showcases the application of efficient search algorithms in AI-driven chat interfaces.

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RAG Application Test Project

RAG Application Test

This project demonstrates the application of RAG (Retrieval-Augmented Generation) in creating advanced AI models, exploring the frontiers of natural language processing.

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