Nando de Freitas

Nando de Freitas added to Favorites and liked 5 months ago
Visualizing saliency maps on Breakout - Duration: 2 minutes, 47 seconds.

by Ziyu Wang

5 months ago
1,211 views
Nando de Freitas added to Favorites and liked 5 months ago
Visualizing saliency maps on Enduro. - Duration: 2 minutes, 47 seconds.

by Ziyu Wang

5 months ago
1,122 views
Nando de Freitas uploaded and added to Deep learning at Oxford 2015 1 year ago
Deep Learning Lecture 15: Deep Reinforcement Learning - Policy search - Duration: 54 minutes.

by Nando de Freitas

1 year ago
15,829 views

Slides available at: https://www.cs.ox.ac.uk/people/nando.defreitas/machinelea...
Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford.
Nando de Freitas uploaded and added to Deep learning at Oxford 2015 1 year ago
Deep Learning Lecture 16: Reinforcement learning and neuro-dynamic programming - Duration: 56 minutes.

by Nando de Freitas

1 year ago
29,847 views

Slides available at: https://www.cs.ox.ac.uk/people/nando.defreitas/machinelea...
Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford.
Nando de Freitas uploaded and added to Deep learning at Oxford 2015 1 year ago
Deep Learning Lecture 14: Karol Gregor on Variational Autoencoders and Image Generation - Duration: 43 minutes.

by Nando de Freitas

1 year ago
13,498 views

Slides available at: https://www.cs.ox.ac.uk/people/nando.defreitas/machinelea...
Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford....
Nando de Freitas uploaded and added to Deep learning at Oxford 2015 1 year ago
Deep Learning Lecture 13: Alex Graves on Hallucination with RNNs - Duration: 53 minutes.

by Nando de Freitas

1 year ago
20,456 views

Slides available at: https://www.cs.ox.ac.uk/people/nando.defreitas/machinelea...
Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford....
Nando de Freitas uploaded and added to Deep learning at Oxford 2015 1 year ago
Deep Learning Lecture 12: Recurrent Neural Nets and LSTMs - Duration: 51 minutes.

by Nando de Freitas

1 year ago
35,753 views

Slides available at: https://www.cs.ox.ac.uk/people/nando.defreitas/machinelea...
Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford.
Nando de Freitas uploaded and added to Deep learning at Oxford 2015 1 year ago
Deep Learning Lecture 11: Max-margin learning, transfer and memory networks - Duration: 58 minutes.

by Nando de Freitas

1 year ago
11,002 views

Slides available at: https://www.cs.ox.ac.uk/people/nando.defreitas/machinelea...
Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford.
Nando de Freitas uploaded and added to Deep learning at Oxford 2015 1 year ago
Deep Learning Lecture 3: Maximum likelihood and information - Duration: 1 hour, 12 minutes.

by Nando de Freitas

1 year ago
26,643 views

Slides available at: https://www.cs.ox.ac.uk/people/nando.defreitas/machinelea...
Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford.
Nando de Freitas uploaded and added to Deep learning at Oxford 2015 1 year ago
Deep Learning Lecture 10: Convolutional Neural Networks - Duration: 50 minutes.

by Nando de Freitas

1 year ago
57,194 views

Slides available at: https://www.cs.ox.ac.uk/people/nando.defreitas/machinelea...
Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford.
Nando de Freitas uploaded and added to Deep learning at Oxford 2015 1 year ago
Deep Learning Lecture 6: Optimization - Duration: 58 minutes.

by Nando de Freitas

1 year ago
13,330 views

Slides available at: https://www.cs.ox.ac.uk/people/nando.defreitas/machinelea...
Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford.
Nando de Freitas uploaded and added to Deep learning at Oxford 2015 1 year ago
Deep Learning Lecture 2: linear models - Duration: 48 minutes.

by Nando de Freitas

1 year ago
36,525 views

Slides available at: https://www.cs.ox.ac.uk/people/nando.defreitas/machinelea...
Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford.
Nando de Freitas uploaded and added to Deep learning at Oxford 2015 1 year ago
Deep learning Lecture 7: Logistic regression, a Torch approach - Duration: 44 minutes.

by Nando de Freitas

1 year ago
13,879 views

Slides available at: https://www.cs.ox.ac.uk/people/nando.defreitas/machinelea...
Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford.
Nando de Freitas uploaded and added to Deep learning at Oxford 2015 1 year ago
Deep Learning Lecture 4: Regularization, model complexity and data complexity (part 1) - Duration: 40 minutes.

by Nando de Freitas

1 year ago
15,723 views

Slides available at: https://www.cs.ox.ac.uk/people/nando.defreitas/machinelea...
Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford.
Nando de Freitas uploaded and added to Deep learning at Oxford 2015 1 year ago
Deep Learning Lecture 9: Neural networks and modular design in Torch - Duration: 53 minutes.

by Nando de Freitas

1 year ago
16,595 views

Slides available at: https://www.cs.ox.ac.uk/people/nando.defreitas/machinelea...
Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford.
Nando de Freitas uploaded and added to Deep learning at Oxford 2015 1 year ago
Deep Learning Lecture 5: Regularization, model complexity and data complexity (part 2) - Duration: 58 minutes.

by Nando de Freitas

1 year ago
12,653 views

Slides available at: https://www.cs.ox.ac.uk/people/nando.defreitas/machinelea...
Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford.
Nando de Freitas uploaded and added to Deep learning at Oxford 2015 1 year ago
Deep Learning Lecture 8: Modular back-propagation, logistic regression and Torch - Duration: 52 minutes.

by Nando de Freitas

1 year ago
14,186 views

Slides available at: https://www.cs.ox.ac.uk/people/nando.defreitas/machinelea...
Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford.
Nando de Freitas subscribed to a channel 1 year ago
Hugo Larochelle - Channel

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Nando de Freitas added 1 video to Talks and tutorials 1 year ago
4 videos Play all

Talks and tutorials - Playlist

by Nando de Freitas

1:13:46
Nando de Freitas Lecture 2

1:05:57
Nando de Freitas Lecture 3

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Nando de Freitas uploaded and added to Deep learning at Oxford 2015 1 year ago
Deep Learning Lecture 1: Introduction - Duration: 52 minutes.

by Nando de Freitas

1 year ago
116,905 views

Slides available at: https://www.cs.ox.ac.uk/people/nando.defreitas/machinelea...
Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford.
Nando de Freitas created Deep learning at Oxford 2015 1 year ago
16 videos Play all

Deep learning at Oxford 2015 - Playlist

by Nando de Freitas

56:04
Deep Learning Lecture 16: Reinforcement learning and neuro-dynamic programming

54:40
Deep Learning Lecture 15: Deep Reinforcement Learning - Policy search

View full playlist (16 videos)
Nando de Freitas liked a video 2 years ago
ICLR14 Invited Talk: Vincent Vanhoucke: "Learning visual representations at scale" - Duration: 34 minutes.

by ICLR

2 years ago
1,766 views

ICLR 2014 Invited Talk: Vincent Vanhoucke
"Learning visual representations at scale"
Nando de Freitas subscribed to a channel 2 years ago
ICLR - Channel

38 videos

Videos from the International Conference on Learning Representations, ICLR.

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Nando de Freitas liked a video 3 years ago
A Bayesian Interactive Optimization Approach to Procedural Animation Design - Duration: 4 minutes, 36 seconds.

by Eric Brochu

5 years ago
2,051 views

My video for the 2010 Symposium on Computer Animation.

In this paper, we present an optimization method for setting parameters of a procedural fluid animation system by showing the user examples o...
Nando de Freitas uploaded and added to Machine Learning 2013 3 years ago
Machine learning - Markov chain Monte Carlo (MCMC) II - Duration: 39 minutes.

by Nando de Freitas

3 years ago
11,247 views

Metropolis-Hastings algorithm. Application to logistic regression.
Slides available at: http://www.cs.ubc.ca/~nando/540-2013/lectures.html
Course taught in 2013 at UBC by Nando de Freitas
Nando de Freitas uploaded a video 3 years ago
Machine learning - Importance sampling and MCMC I - Duration: 1 hour, 16 minutes.

by Nando de Freitas

3 years ago
20,625 views

Importance sampling and Markov chain Monte Carlo (MCMC). Application to logistic regression.
Slides available at: http://www.cs.ubc.ca/~nando/540-2013/lectures.html
Course taught in 2013 at UBC by ...

Nando de Freitas

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Visualizing saliency maps on Breakout - Duration: 2 minutes, 47 seconds.

Visualizing saliency maps on Enduro. - Duration: 2 minutes, 47 seconds.

Deep Learning Lecture 15: Deep Reinforcement Learning - Policy search - Duration: 54 minutes.

Deep Learning Lecture 16: Reinforcement learning and neuro-dynamic programming - Duration: 56 minutes.

Deep Learning Lecture 14: Karol Gregor on Variational Autoencoders and Image Generation - Duration: 43 minutes.

Deep Learning Lecture 13: Alex Graves on Hallucination with RNNs - Duration: 53 minutes.

Deep Learning Lecture 12: Recurrent Neural Nets and LSTMs - Duration: 51 minutes.

Deep Learning Lecture 11: Max-margin learning, transfer and memory networks - Duration: 58 minutes.

Deep Learning Lecture 3: Maximum likelihood and information - Duration: 1 hour, 12 minutes.

Deep Learning Lecture 10: Convolutional Neural Networks - Duration: 50 minutes.

Deep Learning Lecture 6: Optimization - Duration: 58 minutes.

Deep Learning Lecture 2: linear models - Duration: 48 minutes.

Deep learning Lecture 7: Logistic regression, a Torch approach - Duration: 44 minutes.

Deep Learning Lecture 4: Regularization, model complexity and data complexity (part 1) - Duration: 40 minutes.

Deep Learning Lecture 9: Neural networks and modular design in Torch - Duration: 53 minutes.

Deep Learning Lecture 5: Regularization, model complexity and data complexity (part 2) - Duration: 58 minutes.

Deep Learning Lecture 8: Modular back-propagation, logistic regression and Torch - Duration: 52 minutes.

Hugo Larochelle - Channel

Talks and tutorials - Playlist

Nando de Freitas Lecture 2

Nando de Freitas Lecture 3

Deep Learning Lecture 1: Introduction - Duration: 52 minutes.

Deep learning at Oxford 2015 - Playlist

Deep Learning Lecture 16: Reinforcement learning and neuro-dynamic programming

Deep Learning Lecture 15: Deep Reinforcement Learning - Policy search

ICLR14 Invited Talk: Vincent Vanhoucke: "Learning visual representations at scale" - Duration: 34 minutes.

ICLR - Channel

A Bayesian Interactive Optimization Approach to Procedural Animation Design - Duration: 4 minutes, 36 seconds.

Machine learning - Markov chain Monte Carlo (MCMC) II - Duration: 39 minutes.

Machine learning - Importance sampling and MCMC I - Duration: 1 hour, 16 minutes.

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Nando de Freitas

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Nando de Freitas

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Visualizing saliency maps on Breakout - Duration: 2 minutes, 47 seconds.

Visualizing saliency maps on Enduro. - Duration: 2 minutes, 47 seconds.

Deep Learning Lecture 15: Deep Reinforcement Learning - Policy search - Duration: 54 minutes.

Deep Learning Lecture 16: Reinforcement learning and neuro-dynamic programming - Duration: 56 minutes.

Deep Learning Lecture 14: Karol Gregor on Variational Autoencoders and Image Generation - Duration: 43 minutes.

Deep Learning Lecture 13: Alex Graves on Hallucination with RNNs - Duration: 53 minutes.

Deep Learning Lecture 12: Recurrent Neural Nets and LSTMs - Duration: 51 minutes.

Deep Learning Lecture 11: Max-margin learning, transfer and memory networks - Duration: 58 minutes.

Deep Learning Lecture 3: Maximum likelihood and information - Duration: 1 hour, 12 minutes.

Deep Learning Lecture 10: Convolutional Neural Networks - Duration: 50 minutes.

Deep Learning Lecture 6: Optimization - Duration: 58 minutes.

Deep Learning Lecture 2: linear models - Duration: 48 minutes.

Deep learning Lecture 7: Logistic regression, a Torch approach - Duration: 44 minutes.

Deep Learning Lecture 4: Regularization, model complexity and data complexity (part 1) - Duration: 40 minutes.

Deep Learning Lecture 9: Neural networks and modular design in Torch - Duration: 53 minutes.

Deep Learning Lecture 5: Regularization, model complexity and data complexity (part 2) - Duration: 58 minutes.

Deep Learning Lecture 8: Modular back-propagation, logistic regression and Torch - Duration: 52 minutes.

Hugo Larochelle - Channel

Talks and tutorials - Playlist

Nando de Freitas Lecture 2

Nando de Freitas Lecture 3

Deep Learning Lecture 1: Introduction - Duration: 52 minutes.

Deep learning at Oxford 2015 - Playlist

Deep Learning Lecture 16: Reinforcement learning and neuro-dynamic programming

Deep Learning Lecture 15: Deep Reinforcement Learning - Policy search

ICLR14 Invited Talk: Vincent Vanhoucke: "Learning visual representations at scale" - Duration: 34 minutes.

ICLR - Channel

A Bayesian Interactive Optimization Approach to Procedural Animation Design - Duration: 4 minutes, 36 seconds.

Machine learning - Markov chain Monte Carlo (MCMC) II - Duration: 39 minutes.

Machine learning - Importance sampling and MCMC I - Duration: 1 hour, 16 minutes.

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