I am Mohneet Sandhu, a dedicated Data Science professional pursuing my Master's degree at the University of Maryland, College Park, with a targeted graduation in 2026. I have a solid foundation in Applied Statistics and Analytics from NMIMS, where I developed a rigorous understanding of statistical inference, probabilistic modeling, and the mathematical underpinnings of machine learning algorithms.

My core competencies lie in designing and deploying advanced deep learning models, such as Convolutional Neural Networks (CNNs) for computer vision tasks and Recurrent Neural Networks (RNNs) and Transformers for natural language processing. I specialize in implementing state-of-the-art AI techniques, from transfer learning and generative adversarial networks (GANs) to reinforcement learning and self-supervised learning, using frameworks like PyTorch, TensorFlow, and Keras. I am also skilled in feature engineering, dimensionality reduction, and hyperparameter optimization to enhance model performance and scalability.

I am experienced in managing end-to-end machine learning pipelines, leveraging tools such as AWS for cloud computing, Docker for containerization, and Git for version control and collaboration. I have a deep understanding of big data ecosystems, including Hadoop and Spark, and I am adept at SQL and NoSQL databases, enabling robust data extraction, transformation, and loading (ETL) processes.

Passionate about leveraging the latest in AI and machine learning, I thrive on solving complex, data-centric problems and am committed to driving impactful innovations across industries.