Here you can find a curated collection of my skills, projects, and the tools I love using across different domains of Data Science, Machine Learning, Deep Learning, and AI. Check out the badges below representing my expertise in various libraries and technologies.
💻 Role: I'm a Software Engineer specializing in AI/ML, with over 2+ years of professional experience building intelligent systems and scalable machine learning solutions.
🧠 Expertise: My technical strengths span across:
- Machine Learning & Deep Learning
- Natural Language Processing
- Generative AI & Large Language Models (LLMs)
- Model development, evaluation, and deployment
🚀 Current Work: I'm currently working on projects involving Generative AI and LLMs, where I develop and fine-tune models, craft prompts, and build intelligent pipelines that push the boundaries of modern AI.
🎯 Passion: Driven by curiosity and innovation, I enjoy transforming complex problems into practical AI solutions. Whether it’s research, development, or optimization, I thrive at the intersection of software engineering and intelligent systems.
💼 Open to Opportunities: I’m actively exploring opportunities in AI/ML Engineering where I can contribute to impactful projects, collaborate with forward-thinking teams, and grow alongside cutting-edge technologies.
🤝 Let’s Connect
I'm always open to collaborations, discussions, or knowledge sharing around AI, ML, and future technologies. Click below to connect or reach out!
You can find me here:
For traditional machine learning, I use the following libraries and frameworks to build models for classification, regression, clustering, and more:
For deep learning projects, I utilize powerful frameworks and libraries for building neural networks, training models, and deploying them:
For NLP and Generative AI tasks, I leverage the latest models and tools to build chatbots, language models, and more:
In this section, I focus on the libraries and frameworks I use for data manipulation, feature engineering, and the underlying mathematical operations for data science projects:
These are the tools I use to create APIs and interactive applications that communicate with machine learning models or support data analysis:
These are the cloud platforms and services I work with to scale, deploy, and manage machine learning models and data pipelines:
These are the databases I work with to store, manage, and retrieve data for various machine learning and data processing tasks:
These are the development tools and IDEs I use for coding, testing, and deploying Data Science (DS), Machine Learning (ML), Deep Learning (DL), and Generative AI (GenAI) models:
