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Hybrid Model with CNN and LSTM for VMD dataset using Python

Home Page: https://github.com/aaaastark/hybrid-model-with-cnn-lstm-python

cnn-architecture cnn-classification cnn-keras cnn-lstm-models cnn-model data-science deep-learning hybrid-model keras lstm-model lstm-neural-network machine-learning matplotlib numpy pandas python sklearn tensorflow vmd

hybrid-model-with-cnn-lstm-python's Introduction

Author | Research Scientist | Senior AI&ML Engineer | Generative AI Engineer | NVIDIA Developer Program Member

Muhammad Allah Rakha (AAAASTARK), a distinguished Senior AI & ML Engineer, Generative AI Engineer, and Research Scientist, brings 3.5 years of pioneering expertise in Artificial Intelligence, Machine Learning, and Deep Learning, leveraging NVIDIA technology and Oracle-OCI AI certification. A graduate of FAST-NUCES University, Pakistan (BSCS, 2023), he specializes in inventing and deploying cutting-edge ML models, DL algorithms, and NLP systems to solve complex, real-world business challenges.

Muhammad has significantly contributed to the academic and research community as a Researcher for the prestigious "IEEE JSTAR Transactions" journal and as a key contributor to "The AIP Conference Proceedings." His authorship extends to chapters in books published by the renowned Taylor & Francis Group, underscoring his intellectual prowess and deep commitment to advancing the AI landscape.

His role as a certified Oracle-OCI AI expert and an active member of the NVIDIA Developer Program showcases his involvement in pushing the boundaries of AI and GenAI technologies. He has played a pivotal part in the development of autonomous agents, notably contributing to the "GPT-Researcher" project.

As a Researcher at Chongqing University, China, Muhammad specialized in Hyperspectral Image processing, including classification, denoising, and pansharpening, where he drove innovation through extensive research collaborations and data-driven experimentation.

In his capacity as a Generative AI Engineer, Muhammad has designed advanced generative models, optimized system performance, and integrated Retrieval Augmented Generation (RAG) systems to develop next-generation AI applications. His unique ability to collaborate across multidisciplinary teams drives groundbreaking results, advancing the AI/ML ecosystem and fostering future-ready solutions.

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