I specialize in building real-world, end-to-end machine learning and deep learning solutions. My expertise extends to applying these solutions across various domains such as image recognition, predictive modeling, natural language processing, generative AI, optimization, etc.
The purpose of this portfolio is not to provide an exhaustive list of frameworks and tools I have utilized, but rather to showcase a curated selection of projects I have completed. For everyone interested in a comprehensive catalogue of all my previous projects or tools, kindly visit my GitHub.
My experience spans the entire end-to-end ml lifecycle, from understanding the problem domain, data gathering and cleaning, to model development, training, tuning, and deployment.
Broad understanding of various aspects of deep learning, including convolutional and recurrent neural networks, generative ai, transfer learning, natural language processing, and more.
I specialize in extracting insights from complex data sets, utilizing statistical techniques and algorithms to analyze trends, make predictions, and inform decision-making processes.