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Student & Researcher | ML DL AI NS
Machine Learning (ML) is a subfield of Artificial Intelligence that involves the development of algorithms and models that enable computer systems to automatically learn from data and improve their performance over time without being explicitly programmed. ML systems use statistical techniques to identify patterns and relationships in large datasets, and then use that information to make predictions or decisions. The goal of ML is to enable computers to learn from experience and make decisions or predictions that are as accurate as possible. The applications of ML are vast and range from natural language processing and image recognition to predictive analytics and personalized recommendations.
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A feedback loop is a process where the output of a system is fed back as input, creating a continuous cycle of cause and effect. These loops can be found…
The Hopfield network, introduced by John Hopfield in 1982, is a recurrent neural network model inspired by the way memories might be stored in the brain. Unlike traditional computer memory,…
Bioelectrical signal calibration holds immense potential for personalized and targeted COPD treatment. Here are some exciting research areas: Here are some specific research papers on these topics: Regeneration Research Papers…
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Description This book covers an introduction to convex optimization, one of the powerful and tractable optimization problems that can be efficiently solved on a computer. The goal of the book…
Introduction: Delayed learning development can be a significant challenge for many students, impacting their academic success and overall quality of life. While there are a variety of interventions and treatments…