Machine and Deep Learning
Machine learning is more than just API calls to scikit-learn and TensorFlow, I deeply understand model architectures and their optimal use cases.
Machine learning is more than just API calls to scikit-learn and TensorFlow, I deeply understand model architectures and their optimal use cases.
I've leveraged virtual servers to automate script execution, train and deploy models, and manage data storage, while seamlessly integrating with databases for efficient data handling.
I transform unstructured text data into actionable insights using advanced NLP techniques, from sentiment analysis to custom language models, tailored to specific domain needs.
Specializing in automating the end-to-end machine learning lifecycle, I integrate MLOps and CI/CD practices to ensure seamless, reliable, and scalable model deployment.
I've designed robust ETL pipelines to ensure clean, structured data from diverse sources, enabling efficient processing and analysis across the organization.
I consistently utilize Git for all my projects and Docker for containerization, ensuring smooth teamwork and consistent development environments.