ML Concepts – Optimization Algorithm for Training Neural Network Model

Optimizers are algorithms or methods used to change the attributes of your neural network such as weights and learning rate in order to reduce the losses.• Gradient Descent• Stochastic Gradient Descent• Mini-Batch Gradient Descent• Momentum• Nesterov Accelerated Gradient• Adagrad• AdaDelta• Adam (Adaptive Moment Estimation) About The Author Dr. Pranay Jha Dr. Pranay Jha is a…

Optimizers are algorithms or methods used to change the attributes of your neural network such as weights and learning rate in order to reduce the losses.
• Gradient Descent
• Stochastic Gradient Descent
• Mini-Batch Gradient Descent
• Momentum
• Nesterov Accelerated Gradient
• Adagrad
• AdaDelta
• Adam (Adaptive Moment Estimation)

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Architect’s Toolkit

About the Author

Dr. Pranay Jha is a Cloud and AI Consultant with 18+ years of experience in hybrid cloud, virtualization, and enterprise infrastructure transformation. He specializes in VMware technologies, multi-cloud strategy, and Generative AI solutions. He holds a PhD in Computer Applications with research focused on Cloud and AI, has published multiple research papers, and has been a VMware vExpert since 2016 and a VMUG Community Leader.

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