I am an experienced AI Engineer with 10+ years of experience building and deploying machine learning models at scale. I specialize in deep learning, natural language processing, image processing, object detection, and computer vision. I have a proven track record of delivering high-impact AI solutions using PyTorch, TensorFlow, and cloud platforms. I am adept at translating business requirements into technical solutions and optimizing model performance in production environments.
I have a strong history of collaborating with cross-functional teams to integrate AI features into production systems and continuously improving model accuracy and latency. I thrive in fast-paced environments and enjoy turning complex data challenges into practical, scalable AI solutions.
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An enterprise-grade AI-powered leaf disease detection system featuring a dual-interface architecture: a FastAPI backend service and an interactive Streamlit web application. Built with Meta’s Llama Vision models via Groq API, this system provides accurate disease identification, severity assessment, and actionable treatment recommendations for agricultural and horticultural applications.
This is a simple machine learning project using classifiers for predicting factors which affect student grades, using data from CSV file
In this Project, a dataset which has students from nationalities, different grade levels and also soe determining factors like, number of hands raised, nuber attendances, number of hours studied etc. is used, which is a CSV File.
And a few different classifiers and ML models have been used to get the most accurate predictions of which factors, affect the marks of students.
A few visual aids like graphs and confusion matrix have been created, to show the results. Also additional heatmaps and other charts have been added to further demonstrate how data modelling and engineering works.
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