100 Best Deep Belief Network Videos

Deep Belief Network

dbnMerge1 [63x Apr 2015]

NAIP Deep Learning Demo Video

NAIP Deep Learning Demo Video This video explains the use of the Deep Belief Network based learning framework for the delineation of tree-cover areas in the NAIP dataset. From: ideepbasu007 Views: 2 0 ratings Time: 07:05 More in People & Blogs
Deep Learning Lecture 12: Recurrent Neural Nets and LSTMs

Deep Learning Lecture 12: Recurrent Neural Nets and LSTMs Slides available at: https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/ Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford. From: Nando de Freitas Views: 1469 19…
Simon Osindero, A.I. Architect, Flickr – RE.WORK Deep Learning Summit 2015

Simon Osindero, A.I. Architect, Flickr – RE.WORK Deep Learning Summit 2015 This presentation took place at the Deep Learning Summit in San Francisco on 29-30 January 2015. https://www.re-work.co/events/deep-learning-sanfrancisco-2015 ‘Pixels, Parks, Birds, and Beauty’… From: RE.WORK …
Deep learning Lecture 7: Logistic regression, a Torch approach

Deep learning Lecture 7: Logistic regression, a Torch approach Slides available at: https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/ Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford. From: Nando de Freitas Views: 871 …
Deep Learning Lecture 8: Modular back-propagation, logistic regression and Torch

Deep Learning Lecture 8: Modular back-propagation, logistic regression and Torch Slides available at: https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/ Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford. From: Nando de…
Deep Learning Lecture 4: Regularization, model complexity and data complexity (part 1)

Deep Learning Lecture 4: Regularization, model complexity and data complexity (part 1) Slides available at: https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/ Course taught in 2015 at the University of Oxford by Nando de Freitas with great help from Brendan Shillingford. From: Nando…
NLP and Deep Learning: introduction – Session I

NLP and Deep Learning: introduction – Session I Stockholm Natural Language Processing Meetup www.meetup.com/Stockholm-Natural-Language-Processing-Meetup/events/219787462/ In this session, Roelof Pieters will present about NLP and … From: graph ael Views: 506 6 ratings Time: 02:29:06 More…
Legowelt – Codex Arpolxtinus

Legowelt – Codex Arpolxtinus https://cremeorganization.bandcamp.com/album/there-is-no-authority-but-yourself-15-years-creme-organization-part-1-free ‘Ok, so 15 years in this invigorating game is enough to get us all teary-eyed… From: ninauploadz Views: 468 7 ratings Time: 06:32 More…
ASOK – Edge #2

ASOK – Edge #2 https://cremeorganization.bandcamp.com/album/there-is-no-authority-but-yourself-15-years-creme-organization-part-1-free ‘Ok, so 15 years in this invigorating game is enough to get us all teary-eyed… From: ninauploadz Views: 297 9 ratings Time: 07:35 More in Music…
Deep Beliefs Network- Number recognition

Deep Beliefs Network- Number recognition Group Optimus Prime 3.5 presentation on our project for Introduction to Robotics EGN4060. In this video we describe our program, how it runs and the results of our deep belief network. From: Sirgillif Views: 28 0 ratings Time: 03:47 More in People…
ICRA2015 Automatic Search Supplementary Video

ICRA2015 Automatic Search Supplementary Video Automatic object searching involves concatenation of several capabilities including object identification, obstacle avoidance, path planning, and navigation. This is one of the essential skills… From: B. Tian Views: 12 0 ratings Time: 02:22 …
Getting Started with Deep Learning and Python

Getting Started with Deep Learning and Python Interested in deep learning but don’t know where to start? In this tutorial I’ll show you how to utilize Python and the nolearn package to create Deep Belief Network to classify handwritten… From: Adrian Rosebrock Views: 4733 23 ratings…
Deep learning

Deep learning Deep learning is a set of algorithms in machine learning that attempt to model high-level abstractions in data by using model architectures composed of multiple non-linear transformations…. From: Audiopedia Views: 110 0 ratings Time: 25:43 More in Education
[14][5]OPTIONAL VIDEO RBMs are infinite sigmoid belief nets (17 mins)

[14][5]OPTIONAL VIDEO RBMs are infinite sigmoid belief nets (17 mins) Neural Networks for Machine Learning by Geoffrey Hinton Source: ttps://class.coursera.org/neuralnets-2012-001. From: Minh Anh Truong Views: 38 0 ratings Time: 17:12 More in People & Blogs
Big Data Deep Learning Challenges and Perspectives

Big Data Deep Learning Challenges and Perspectives Final Year IEEE Projects for BE, B.Tech, ME, M.Tech,M.Sc, MCA & Diploma Students latest Java, .Net, Matlab, NS2, Android, Embedded,Mechanical, Robtics, VLSI, Power Electronics, IEEE projects… From: Ecway Karur Views: 20 0 ratings Time: …
DIY Early Prototype Smart Microscope / Tricorder

DIY Early Prototype Smart Microscope / Tricorder A guide on how the combination of three technologies: a smartphone, a microscope, and machine learning software creates an early-stage smart microscope or tricorder! A tool that may eventually… From: Catalyst Frame Views: 206 2 ratings Time: …
Rule 4 Deep Learning English Powerful English Lessons

Rule 4 Deep Learning English Powerful English Lessons Hi, this is A.J. again, director of “Effortless English”. Welcome to the fourth rule for speaking excellent English. Now, this rule is also very simple. In fact, all of these rules are simple,… From: Kênh H?c Ti?ng Anh…
The Power of Belief

The Power of Belief In this video, Jennipher goes into just how deep the power of belief is. Whether you belief system is faith or science, examples are shown to show just how powerful your thoughts are in manifesting… From: missjennipher Views: 94 3 ratings Time: 05:44 More in People…
Interactive Tool for Deep Learning

Interactive Tool for Deep Learning This is a prototype of an interactive tool that enables creating artificial neural networks using visual programming paradigm. From: Milan Lajtoš Views: 617 12 ratings Time: 02:56 More in Science & Technology
Deep learning by Mateusz Bu?kiewicz

Deep learning by Mateusz Bu?kiewicz Mateusz Bu?kiewicz presents an overview of Deep Learning, state-of-the-art, powerful way to do machine learning. With massive amounts of computational power, machines can now recognise objects. From: Szymon Sobczak Views: 215 4 ratings Time: 16:17 More…
#3: Dog Finder – 100 Ways to Use Jetpac Deep Belief

#3: Dog Finder – 100 Ways to Use Jetpac Deep Belief Teach your phone to recognize your dog! Teach it to recognize any object using the Jetpac Deep Belief framework running on the phone. See the future – this is the latest in Object Recognition… From: JetpacApp Views: 229 1 ratings Time: …
#2: Jetpac Sunglass Finder – 100 Ways to Use Jetpac Deep Belief

#2: Jetpac Sunglass Finder – 100 Ways to Use Jetpac Deep Belief Teach your phone to recognize your sunglasses! Teach your iPhone to see! Teach it to recognize any object using the Jetpac Deep Belief framework running on the phone. See the future – this… From: JetpacApp Views: 154 1 ratings…
Flat Space, Deep Learning (Part 1)

Flat Space, Deep Learning (Part 1) Biology Leadership Conference Community Webinar with Dr. Eric Mazur – April 11, 2014 Our Biology Leadership Conference Community hosts regular webinars that help sustain the teaching and … From: Pearson North America Views: 164 0 ratings Time: 25:19 More…
[ESA DSSS]: Deep Neural Network Acoustic Models for Automatic Speech Recognition

[ESA DSSS]: Deep Neural Network Acoustic Models for Automatic Speech Recognition Title: Deep Neural Network Acoustic Models for Automatic Speech Recognition (ASR) By: Dr. Abdel-rahman Mohamed Abstract: In the past few years, Deep Neural Networks (DNNs) have achieved the. From: ESA UofT Views:…
Deep Learning – Jürgen Schmidhuber – #1

Deep Learning – Jürgen Schmidhuber – #1 Slides: http://goo.gl/WtAFYv züri ML meetup #1, february 25th 2014 Jürgen Schmidhuber, Director of the Swiss AI Lab IDSIA Deep Learning We’re very excited to have one of the world experts… From: Zürich Machine Learning and Data Science Meetup …
Jetpac Spotter Deep Belief Object Recognition App

Jetpac Spotter Deep Belief Object Recognition App Now your iPhone can see! Point your iPhone at any object and Spotter will tell you what it thinks it is. See the future – this is the latest in Deep Belief Object Recognition, on a phone… From: JetpacApp Views: 1005 5 ratings Time: 02:11 …
Deep Belief Network first layer (20×20) pre-training phase CIFAR-10

Deep Belief Network first layer (20×20) pre-training phase CIFAR-10 From: Andrey Cizov Views: 93 0 ratings Time: 00:41 More in People & Blogs
Deep Belief Network first layer before pre-training phase MNIST

Deep Belief Network first layer before pre-training phase MNIST From: Andrey Cizov Views: 236 1 ratings Time: 00:51 More in People & Blogs
Query adaptive image search using hash codes

Query adaptive image search using hash codes ABSTRACT: Scalable image search based on visual similarity has been an active topic of research in recent years. State-of-the-art solutions often use hashing methods to embed high-dimensional… From: tchnopundits Views: 174 2 ratings Time: 00:47 …
Deep Learning: Lecture 4

Deep Learning: Lecture 4 Deep Learning and Neural Net short course by Kevin Duh at the Nara Institute of Science and Technology (Jan 2014). Lecture 4: Advanced topics in Optimization. Course website: http://cl.naist.jp/~ke… From: Kevin Duh Views: 2199 12 ratings Time: 01:27:34 More in …
Deep Learning: Lecture 1

Deep Learning: Lecture 1 Deep Learning and Neural Net short course by Kevin Duh at the Nara Institute of Science and Technology (Jan 2014). Lecture 1: Machine learning & Neural Net background. Course website: … From: Kevin Duh Views: 16588 105 ratings Time: 01:28:54 More in Education…
Scientific Dreamz Of U – Deep Belief Network (Neural Grid Optimization)

Scientific Dreamz Of U – Deep Belief Network (Neural Grid Optimization) The world around us can be described at many levels; aural intensities, dimensional edges, objective parts, non-objects, and beyond. The prospect of learning hierarchical models which simultaneousl. From: hurfyd Views: 5653…
Neural networks [7.2] : Deep learning – difficulty of training

Neural networks [7.2] : Deep learning – difficulty of training From: Hugo Larochelle Views: 3327 13 ratings Time: 08:24 More in Science & Technology
3. Learning Sigmoid Belief Nets

3. Learning Sigmoid Belief Nets Video from Coursera – University of Toronto – Course: Neural Networks for Machine Learning: https://www.coursera.org/course/neuralnets. From: Artificial Intelligence Courses Views: 650 2 ratings Time: 11:26 More in Education
1. The Ups and Downs of Back Propagation

1. The Ups and Downs of Back Propagation Video from Coursera – University of Toronto – Course: Neural Networks for Machine Learning: https://www.coursera.org/course/neuralnets. From: Artificial Intelligence Courses Views: 205 1 ratings Time: 09:54 More in Education
1. Boltzmann Machine Learning

1. Boltzmann Machine Learning Video from Coursera – University of Toronto – Course: Neural Networks for Machine Learning: https://www.coursera.org/course/neuralnets. From: Artificial Intelligence Courses Views: 1433 0 ratings Time: 12:16 More in Education
3. Hopfield Nets with Hidden Units

3. Hopfield Nets with Hidden Units Video from Coursera – University of Toronto – Course: Neural Networks for Machine Learning: https://www.coursera.org/course/neuralnets. From: Artificial Intelligence Courses Views: 342 0 ratings Time: 09:40 More in Education
Deep belief network generating faces(2)

Deep belief network generating faces(2) Deep belief network generating faces. Top layer neuron activations are shown on the right, the face ‘archetype’ in the middle, and random samples of the lower layers on the left. This is a… From: Tai Skoropada Views: 520 2 ratings Time: 00:39…
Deep belief network generating faces

Deep belief network generating faces These faces are generated by a 3 layer deep belief network of stacked RBMs, the pixels on the right are the activations of the top layer neurons. The number of neurons in the layers in the… From: Tai Skoropada Views: 542 5 ratings Time: 03:33 More in …
Can ‘Deep Learning’ Offer Deep Insights about Visual Representation? – Bay Area Vision Meeting

Can ‘Deep Learning’ Offer Deep Insights about Visual Representation? – Bay Area Vision Meeting Deep network architectures and learning algorithms have a long and storied history in computational neuroscience going back to Fukushima (1980) and Selfridge (1959). What have we learned since……
Classifying Digits with Deep Belief Networks

Classifying Digits with Deep Belief Networks Classifying Digits with Deep Belief Networks using the Accord Machine Learning libraries and the Tsunami IDE. From: Tsunami IDE Views: 626 6 ratings Time: 04:19 More in Science & Technology
Text recognition at the bus station using deep learning.

Text recognition at the bus station using deep learning. We train artificial neural networks (using deep learning) with videos from Geneva’s bus stations. The end result is a system able to detect and read characters at any station, as an aid for… From: Juan Diego Gómez Views: 145 1…
Hyperopt: A Python library for optimizing machine learning algorithms; SciPy 2013

Hyperopt: A Python library for optimizing machine learning algorithms; SciPy 2013 Hyperopt: A Python library for optimizing the hyperparameters of machine learning algorithms Authors: Bergstra, James, University of Waterloo; Yamins, Dan, Massachusetts Institute of Technology;… From: Enthought …
Geoff Hinton – Recent Developments in Deep Learning

Geoff Hinton – Recent Developments in Deep Learning Geoff Hinton presents as part of the UBC Department of Computer Science’s Distinguished Lecture Series, May 30, 2013. Professor Hinton was awarded the 2011 Herzberg Canada Gold Medal for … From: UBCCPSC Views: 43321 353 ratings Time: …
10-701 Student Presentation – Combine cRBM and CNN for Object Recognition

10-701 Student Presentation – Combine cRBM and CNN for Object Recognition Xinghai Hu, Minghao Ruan, Han Li We will present a novel deep network structure that combines the Convolutional Neural Network (CNN) and novel Convolutional Restricted Boltzmann Machine … From: Alex Smola Views: 350 2…
Tutorial-Bayesian Belief Networks

Tutorial-Bayesian Belief Networks Chapter 1, Strategic Economic Decision-Making: Using Bayes Belief Networks to Make Complex Decisions. From: Jeff Grover Views: 513 0 ratings Time: 01:22 More in Education
ERMITES_2012_M_Van_Gerven : « Percept Decoding with Sparse Latent Variable Models »

ERMITES_2012_M_Van_Gerven : « Percept Decoding with Sparse Latent Variable Models » Functional MRI has an exquisite spatial resolution which offers a unique window into the brain . Using sophisticated machine learning techniques, researchers have shown that visual percepts… From: …
ERMITES_2012_X_Halkias: «General Sparse Penalty in Deep Belief Networks Towards Domain Adaptation»

ERMITES_2012_X_Halkias: «General Sparse Penalty in Deep Belief Networks Towards Domain Adaptation» The goal of the talk is to explore the efficacy of DBNs. Deep Belief Networks (DBN) have been successfully applied on popular machine learning tasks. Specifically, when applied on hand-written… …
ERMITES_2012_T_Hannagan : « Symmetry networks: three applications to cognitive modeling »

ERMITES_2012_T_Hannagan : « Symmetry networks: three applications to cognitive modeling » Symmetry networks [1] are feedforward networks whose outputs are invariant under some transformation of the inputs. I will describe three different encounters with symmetry networks in visual… From: …
ECE 804 – Fall 2012 – Lecture 004 with Dr. Yann LeCun

ECE 804 – Fall 2012 – Lecture 004 with Dr. Yann LeCun “Deep Learning of Invariant Feature Hierarchies” Fundamental problems in science and engineering have become increasingly interdisciplinary, requiring knowledge and expert input from several… From: ecencsu Views: 1178 7 ratings…
Sample: Accord.NET Deep Neural Networks

Sample: Accord.NET Deep Neural Networks Learning Deep Neural Networks using Restricted Boltzmann Machines in the Accord.NET Framework. Please turn the annotations on for a complete description of the video. In the video, intermediate… From: César Roberto de Souza Views: 8170 35 ratings…
Tutorial Bayesian Belief Network Proof

Tutorial Bayesian Belief Network Proof This is a proof of a 5-Node Bayesian Belief Network. www.bayestheorem-qed.com. From: Jeff Grover Views: 3441 6 ratings Time: 07:42 More in Education
Deep Neural Networks for Speech and Image Processing

Deep Neural Networks for Speech and Image Processing AERFAI Summer School on Pattern Recognition in Multimodal Human Interaction – Deep Neural Networks for Speech and Image Processing This is the sixth edition in a series of AERFAI Summer … From: CampusdoMar Views: 18608 106 ratings Time: …
Sheikh Abu Omar: Funny and Deep Belief in the Unseen

Sheikh Abu Omar: Funny and Deep Belief in the Unseen Faith iman paradise believe without seeing everything is unseen for us ALLAH Prophet Mohammed paradise hell fire judgement day we lack ISLAM WAY TO SUCCESS destiny taqwa basira the light of. From: SheikhAbuOmar Views: 249 2 ratings Time: …
Android Application Development

Android Application Development Who are new to Android application development often face an important decision – “what options are available to start developing applications on android”. The primary objective for this webinar… From: Tech Gig Views: 69 0 ratings Time: 16:24 More…
NIPS 2011 Music and Machine Learning Workshop: Modeling the Acoustic Structure of Musical Emotion…

NIPS 2011 Music and Machine Learning Workshop: Modeling the Acoustic Structure of Musical Emotion… International Music and Machine Learning Workshop: Learning from Musical Structure at NIPS 2011 Invited Talk: Modeling the Acoustic Structure of Musical Emotion with Deep Belief Networks… From: …
NIPS 2011 Domain Adaptation Workshop: Training Structured Prediction Models

NIPS 2011 Domain Adaptation Workshop: Training Structured Prediction Models Domain Adaptation Workshop: Theory and Application at NIPS 2011 Invited Talk: Training Structured Prediction Models with Extrinsic Loss Functions by Slav Petrov Slav Petrov is a Research… From: GoogleTechTalks Views:…
Jürgen Schmidhuber at AGI-2011: Fast Deep/Recurrent Nets for AGI Vision

Jürgen Schmidhuber at AGI-2011: Fast Deep/Recurrent Nets for AGI Vision The Fourth Conference on Artificial General Intelligence Mountain View, California, USA August 3-6, 2011 Jürgen Schmidhuber’s short talk on fast deep neural networks at AGI 2011 at Google… From: GoogleTechTalks …
Machine Learning Group (MLG) – Laboratoire d’Apprentissage Automatique de l’ULB

Machine Learning Group (MLG) – Laboratoire d’Apprentissage Automatique de l’ULB The Machine Learning Group (MLG) was founded in 2004 by Prof. G. Bontempi. The MLG is active in several projects (see also here) which cover a wide range of theoretical topics and applied… From: …
Bay Area Vision Meeting: Unsupervised Feature Learning and Deep Learning

Bay Area Vision Meeting: Unsupervised Feature Learning and Deep Learning Bay Area Vision Meeting (more info below) Unsupervised Feature Learning and Deep Learning Presented by Andrew Ng March 7, 2011 ABSTRACT Despite machine learning’s numerous successes,… From: GoogleTechTalks Views:…
Deep Belief Net Test W/ Backprop

Deep Belief Net Test W/ Backprop This is another simple test of how deep-belief-network principles work (like this http://www.youtube.com/watch?v=8BqELwn0biA ), this time trained with the 600 first digits of the training set… From: Rodrigo Guerra Views: 2423 5 ratings Time: 03:21 More in …
Simple Deep Belief Net Test

Simple Deep Belief Net Test This is a very simple implementation that I did in order to better understand how deep-belief-network principles worked in practice. The network has 3 layers with 500, 500 and 2000 nodes respective… From: Rodrigo Guerra Views: 2845 9 ratings Time: 03:04 More in…
The Next Generation of Neural Networks

The Next Generation of Neural Networks Google Tech Talks November, 29 2007 In the 1980’s, new learning algorithms for neural networks promised to solve difficult classification tasks, like speech or object recognition, by learning… From: GoogleTechTalks Views: 390792 1884 ratings Time: …

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