ОБ ЭТОМ ПОДКАСТЕ 🔗
Deep Learning (DL) has attracted much interest in a wide range of applications such as image recognition, speech recognition, and artificial intelligence, both from academia and industry. This lecture introduces the core elements of neural networks and deep learning, it comprises:
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(multilayer) perceptron, backpropagation, fully connected neural networks
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loss functions and optimization strategies
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convolutional neural networks (CNNs)
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activation functions
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regularization strategies
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common practices for training and evaluating neural networks
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visualization of networks and results
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common architectures, such as LeNet, Alexnet, VGG, GoogleNet
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recurrent neural networks (RNN, TBPTT, LSTM, GRU)
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deep reinforcement learning
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unsupervised learning (autoencoder, RBM, DBM, VAE)
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generative adversarial networks (GANs)
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weakly supervised learning
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applications of deep learning (segmentation, object detection, speech recognition, ...)
The accompanying exercises will provide a deeper understanding of the workings and architecture of neural networks.
Частота обновления:
every 14 hours
Средняя продолжительность аудио:
14 minutes
Видео подкаст
английский
США
52 серий
с 13 апреля 2020 г.
serial
САМЫЕ СТАРЫЕ ЭПИЗОДЫ 🔗
Deep Learning - Introduction Part 2
This video introduces the topic of Deep Learning by showing several well-known examples from FAU.
Video References:
Lex Fridman's Channel
Car Scene
Mitotic Dataset
Further Reading
A gentle Introduction to Deep Learning
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ПРЕДЫДУЩИЕ ЭПИЗОДЫ 🔗
Deep Learning - Introduction Part 2
This video introduces the topic of Deep Learning by showing several well-known examples from FAU.
Video References:
Lex Fridman's Channel
Car Scene
Mitotic Dataset
Further Reading
A gentle Introduction to Deep Learni…
Deep Learning - Introduction Part 3
This video introduces the topic of Deep Learning and discusses challenges and future directions.
Video References:
Lex Fridman's Channel
Further Reading
A gentle Introduction to Deep Learning
Deep Learning - Introduction Part 3
This video introduces the topic of Deep Learning and discusses challenges and future directions.
Video References:
Lex Fridman's Channel
Further Reading
A gentle Introduction to Deep Learning
Deep Learning - Introduction Part 4
This video introduces the topic of Deep Learning by defining the course's notation, introducing fundamental principles of Pattern Recognition, and a short review of the perceptron.
Video References:
Lex Fridman's Channel
Further Reading
A gentl…
Deep Learning - Introduction Part 4
This video introduces the topic of Deep Learning by defining the course's notation, introducing fundamental principles of Pattern Recognition, and a short review of the perceptron.
Video References:
Lex Fridman's Channel
&nbs…
Deep Learning - Introduction Part 5
This video introduces the topic of Deep Learning and presents the course's requirements, grading procedures, and summarises the first unit.
Video References:
Lex Fridman's Channel
References
[1] David Silver, Julian Schrittwieser, Karen Simonya…
Отказ от ответственности: Подкаст и иллюстрации, встроенные в эту страницу, взяты из Prof. Dr.-Ing. Andreas Maier, который является собственностью его владельца и не связан или не одобрен Listen Notes, Inc.
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