Artificial neural networks | Classification algorithms | Computational statistics
An artificial neural network (ANN) combines biological principles with advanced statistics to solve problems in domains such as pattern recognition and game-play. ANNs adopt the basic model of neuron analogues connected to each other in a variety of ways. (Wikipedia).
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In this video, I present some applications of artificial neural networks and describe how such networks are typically structured. My hope is to create another video (soon) in which I describe how neural networks are actually trained from data.
From playlist Machine Learning
This lecture gives an overview of neural networks, which play an important role in machine learning today. Book website: http://databookuw.com/ Steve Brunton's website: eigensteve.com
From playlist Intro to Data Science
17 Machine Learning: Artificial Neural Networks
Let's demystify artificial neural networks with an accessible lecture on artificial neural networks, including the architecture, parameters, hyperparameters, and training with back-propagation and steepest descent. A demonstration workflow is available at https://git.io/fjlao. Try out a
From playlist Machine Learning
This lecture discusses artificial intelligence (AI) in the context of data science and machine learning. Book website: http://databookuw.com/ Steve Brunton's website: eigensteve.com
From playlist Intro to Data Science
Neural Network Architectures & Deep Learning
This video describes the variety of neural network architectures available to solve various problems in science ad engineering. Examples include convolutional neural networks (CNNs), recurrent neural networks (RNNs), and autoencoders. Book website: http://databookuw.com/ Steve Brunton
From playlist Data Science
But what is an Artificial Neuron? | Artificial Neurons decoded
#ArtificialNeuron #perceptron #deeplearning In this video, I have explained the concept of an artificial neuron from a mathematical point of view. This video will help the beginners to understand the building blocks of the modern day deep neural nets. You will get to know what are the dif
From playlist Learn Machine Learning Concepts
Introducing Artificial Neural Networks in SPSS | Analysis and Interpretation
In this video, I will demonstrate how to run an artificial neural network (ANN) analysis in SPSS and interpret the output. The concepts discussed include multilevel perceptron ANN, deep learning, hidden layer, accuracy, specificity, sensitivity, training, and testing. Related papers and
From playlist Clustering
Neural networks and the brain: from the retina to semantic cognition - Surya Ganguli
Surya Ganguli research spans the fields of neuroscience, machine learning and physics, focusing on understanding and improving how both biological and artificial neural networks learn striking emergent computations. In this talk Dr. Ganguli shows how a synthesis of machine learning, neuros
From playlist Wu Tsai Neurosciences Institute
8ECM Plenary Lecture: Alfio Quarteroni
From playlist 8ECM Plenary Lectures
Neural Network In Artificial Intelligence | Neural Network Explained | Neural Network | Simplilearn
Neural Network in artificial intelligence by simplilearn is a tutorial based on the fundamentals of neural network programming. In this video, we are going to discuss the role of *Neural Network in Artificial Intelligence* in different fields.This video will give idea on how neural network
From playlist Deep Learning Tutorial Videos 🔥[2022 Updated] | Simplilearn
8ECM Plenary Lecture: Gitta Kutyniok
From playlist 8ECM Plenary Lectures
Artificial Intelligence, the History and Future - with Chris Bishop
Chris Bishop discusses the progress and opportunities of artificial intelligence research. Subscribe for weekly science videos: http://bit.ly/RiSubscRibe The last five years have witnessed a dramatic resurgence of excitement in the goal of creating intelligent machines. Technology compani
From playlist Ri Talks
Artificial intelligence: success, limits, myths and threats (Lecture 1) by Marc MĂ©zard
INFOSYS-ICTS TURING LECTURES ARTIFICIAL INTELLIGENCE: SUCCESS, LIMITS, MYTHS AND THREATS SPEAKER: Marc Mézard (Director of Ecole normale supérieure - PSL University ) DATE: 06 January 2020, 16:00 to 17:30 VENUE: Chandrasekhar Auditorium, ICTS-TIFR, Bengaluru Lecture 1 (Public Lecture)
From playlist Infosys-ICTS Turing Lectures
Information Service Engineering 2021 Prof. Dr. Harald Sack Karlsruhe Institute of Technology Summer semester 2021 Lecture 10: Basic Machine Learning - 1 4.1 A Brief History of AI - The success story of machine learning - Donald Hebb and the neuron - McCulloch & Pitts and the artificial n
From playlist ISE2021 - Lecture 10 - 23.06.2021
Deep Learning With Python | Deep Learning Tutorial For Beginners | Edureka
** Tensorflow Training: https://www.edureka.co/ai-deep-learning-with-tensorflow ** This video on "Deep Learning with Python" will provide you with detailed and comprehensive knowledge of Deep Learning, How it came into emergence. The various subparts of Data Science, how they are related a
From playlist Deep Learning With TensorFlow Videos
Gilles Wainrib - Transfer Learning and Collaborative AI
Everyday, new deep learning algorithms are trained to solve specific tasks, such as medical images classification. What if we could share and connect those algorithms and create the conditions for a cross-fertilization between these powerful artificial intelligence systems ? In this talk,
From playlist 3rd Huawei-IHES Workshop on Mathematical Theories for Information and Communication Technologies
Neural Networks 1 Neural Units
From playlist Week 5: Neural Networks
