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Category: Algebra

Algebra is a branch of mathematics that deals with abstract systems, known as algebraic structures, and the manipulation of expressions within those systems. It is a generalization of arithmetic that introduces variables and algebraic operations other than the standard arithmetic operations, such as addition and multiplication.

Protected: Course Title: Spiking Neural Networks (SNNs)

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Published May 11, 2024

Categorized as Algebra, Algorithms, Analysis, Analytics, Architechtures, Artificial Intelligence, Bioinfomatics, Biometrics, Blog, Brain Computer Interfaces, Cognition, Computational Neuroscience, Computer Science, Computer Vision, Cybersecurity, Data Mining, Electrical Engineering, Ethical Hacking, Ethics & Law, Government, Linguistics, Machine Learning, Mathematics, Neuroscience, Neuroscientific Analysis Tagged Artificial Intelligence, Cognitive Neuroscience, Data Privacy, Machine Learning, Neural Networks

Linear Algebra A Course For Physicists and Engineers

About this book In order not to intimidate students by a too abstract approach, this textbook on linear algebra is written to be easy to digest by non-mathematicians. It introduces the concepts of vector spaces and mappings between them without dwelling on statements such as theorems and proofs too much. It is also designed to… Continue reading Linear Algebra A Course For Physicists and Engineers

A Deep Learning Overview

Deep learning is a subset of machine learning that involves training artificial neural networks with multiple layers to recognize and classify patterns in data. The term “deep” refers to the fact that these neural networks have many layers, which allows them to learn complex representations of data. In recent years, deep learning has made significant… Continue reading A Deep Learning Overview

Published April 15, 2023

Categorized as Algebra, Algorithms, Architechtures, Artificial Intelligence, Blog, Computer Science, Deep Learning Tagged Artificial Intelligence, convolutional neural networks, Deep Learning, deep learning algorithms, deep learning applications, deep learning architectures (e.g., deep learning challenges, deep learning explainability, deep learning frameworks, deep learning future directions., deep learning in adversarial networks, deep learning in anomaly detection, deep learning in audio processing, deep learning in autonomous vehicles, deep learning in computer vision, deep learning in data analytics, deep learning in deep reinforcement learning, deep learning in drug discovery, deep learning in finance, deep learning in generative models, deep learning in genomics, deep learning in graph data, deep learning in healthcare, deep learning in image recognition, deep learning in language translation, deep learning in natural language processing, deep learning in object detection, deep learning in recommendation systems, deep learning in reinforcement learning, deep learning in robotics, deep learning in self-supervised learning, deep learning in semantic segmentation, Deep Learning in Sentiment Analysis, deep learning in speech recognition, Deep Learning in Time Series Analysis, deep learning in transfer learning, deep learning in unsupervised learning, deep learning model interpretability, deep learning optimization algorithms, deep learning research, deep learning scalability, deep learning training techniques, deep neural architectures, deep neural models, deep neural networks, Machine Learning, Neural Networks, recurrent neural networks, transformer models

_{Melaney Kakkar | Student & Research Scientist}

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