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    Neural Networks

    2 482 курсов
    Backpropagation
    Capsule Networks
    ControlNet
    Convolutional Neural Networks (CNN)
    Feedforward Neural Networks
    Generative Adversarial Networks (GAN)
    Graph Neural Networks (GNN)
    Multilayer Perceptron
    Multilayer Perceptrons
    Neural Network Architecture
    Recurrent Neural Networks (RNN)
    Variational Autoencoder (VAE)
    LLM Post-Training - Lecture 14
    MIT HAN Lab

    LLM Post-Training - Lecture 14

    Variational Audio-Visual Representation Learning - Lecture 34
    AI Doctoral Academy

    Variational Audio-Visual Representation Learning - Lecture 34

    Machine Learning - Lecture 18
    UofU Data Science

    Machine Learning - Lecture 18

    Machine Learning - Lecture 19
    UofU Data Science

    Machine Learning - Lecture 19

    Machine Learning - Lecture 19
    UofU Data Science

    Machine Learning - Lecture 19

    Machine Learning - Lecture 21
    UofU Data Science

    Machine Learning - Lecture 21

    Machine Learning - Lecture 23
    UofU Data Science

    Machine Learning - Lecture 23

    Machine Learning Fundamentals - Lecture 26
    UofU Data Science

    Machine Learning Fundamentals - Lecture 26

    Classification Methods: KNN, Decision Trees, and Neural Networks - Lecture 28
    UofU Data Science

    Classification Methods: KNN, Decision Trees, and Neural Networks - Lecture 28

    Data Mining: Embeddings and Representations in Machine Learning - Spring 2023
    UofU Data Science

    Data Mining: Embeddings and Representations in Machine Learning - Spring 2023

    Perceptron Algorithm and Mistake Bound Theorem - Lecture 9
    UofU Data Science

    Perceptron Algorithm and Mistake Bound Theorem - Lecture 9

    Perceptron Algorithm and the Novikoff-Block Mistake-Bound Theorem - Lecture 10
    UofU Data Science

    Perceptron Algorithm and the Novikoff-Block Mistake-Bound Theorem - Lecture 10

    The Unreasonable Effectiveness of Mathematics in Large Scale Deep Learning - From Theory to Practice
    Centre for Networked Intelligence, IISc

    The Unreasonable Effectiveness of Mathematics in Large Scale Deep Learning - From Theory to Practice

    What's New and Improved in Wolfram Language Version 14
    Wolfram

    What's New and Improved in Wolfram Language Version 14

    From One Brain to Everyone's Brain
    BUOG SPE Student Chapter

    From One Brain to Everyone's Brain

    The Elusive Generalization: Classical Bounds to Double Descent to Grokking
    Simons Institute

    The Elusive Generalization: Classical Bounds to Double Descent to Grokking

    Networks that Adapt to Intrinsic Dimensionality Beyond the Domain
    Inside Livermore Lab

    Networks that Adapt to Intrinsic Dimensionality Beyond the Domain

    Bayesian Optimization: Exploiting Machine Learning Models, Physics, and Throughput Experiments
    Inside Livermore Lab

    Bayesian Optimization: Exploiting Machine Learning Models, Physics, and Throughput Experiments

    Scaling Up AI: Embedding Physics Modeling into End-to-end Learning and Harnessing Random Projection
    Inside Livermore Lab

    Scaling Up AI: Embedding Physics Modeling into End-to-end Learning and Harnessing Random Projection

    Reduced Order Modeling and Inverse Design of Flexible Structures by Machine Learning
    Inside Livermore Lab

    Reduced Order Modeling and Inverse Design of Flexible Structures by Machine Learning

    Deep Neural Operators with Reliable Extrapolation for Multiphysics and Multiscale Problems
    Inside Livermore Lab

    Deep Neural Operators with Reliable Extrapolation for Multiphysics and Multiscale Problems