Deep Learning
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Deep Learning

À PROPOS DE CE PODCAST 🔗

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:

  • (multilayer) perceptron, backpropagation, fully connected neural networks

  • loss functions and optimization strategies

  • convolutional neural networks (CNNs)

  • activation functions

  • regularization strategies

  • common practices for training and evaluating neural networks

  • visualization of networks and results

  • common architectures, such as LeNet, Alexnet, VGG, GoogleNet

  • recurrent neural networks (RNN, TBPTT, LSTM, GRU)

  • deep reinforcement learning

  • unsupervised learning (autoencoder, RBM, DBM, VAE)

  • generative adversarial networks (GANs)

  • weakly supervised learning

  • 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.

Éducation
Fréquence de mise à jour:
every 14 hours
Durée audio moyenne:
14 minutes
Podcast vidéo
Anglais
États-Unis
52 épisodes
depuis 13 avril 2020
serial
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Deep Learning - Introduction Part 2

Deep Learning - Introduction Part 2

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 
00:18:41
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2 - Deep Learning - Introduction Part 2

2 - Deep Learning - Introduction Part 2

00:18:41
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2 - Deep Learning - Introduction Part 2 2020

2 - Deep Learning - Introduction Part 2 2020

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…
00:18:41
PARTAGER
ENREGISTRER
Deep Learning - Introduction Part 3

Deep Learning - Introduction Part 3

  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   
00:08:48
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3 - Deep Learning - Introduction Part 3

3 - Deep Learning - Introduction Part 3

00:08:48
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3 - Deep Learning - Introduction Part 3 2020

3 - Deep Learning - Introduction Part 3 2020

  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   
00:08:48
PARTAGER
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Deep Learning - Introduction Part 4

Deep Learning - Introduction Part 4

  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…
00:14:48
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4 - Deep Learning - Introduction Part 4

4 - Deep Learning - Introduction Part 4

00:14:48
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4 - Deep Learning - Introduction Part 4 2020

4 - Deep Learning - Introduction Part 4 2020

  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…
00:14:48
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Deep Learning - Introduction Part 5

Deep Learning - Introduction Part 5

  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…
00:06:29
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Avertissement: Le podcast et les illustrations intégrés sur cette page proviennent de Prof. Dr.-Ing. Andreas Maier, qui est la propriété de son propriétaire et n'est ni affilié ni approuvé par Listen Notes, Inc.
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