Neural Networks for Machine Learning

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文档大小：964.3 MB
文档个数：243个文档
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收录时间：2020-01-30
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文档列表

0504 Convolutional nets for object recognition.mp4 24.1 MB
0701 Modeling sequences_ A brief overview.mp4 21.1 MB
1401 Learning layers of features by stacking RBMs.mp4 21.0 MB
1405 OPTIONAL VIDEO_ RBMs are infinite sigmoid belief nets.mp4 20.4 MB
0503 Convolutional nets for digit recognition.mp4 19.4 MB
1202 OPTIONAL VIDEO_ More efficient ways to get the statistics.mp4 17.8 MB
0205 What perceptrons can_t do.mp4 17.4 MB
0802 Modeling character strings with multiplicative connections.mp4 17.4 MB
0801 A brief overview of Hessian Free optimization.mp4 17.0 MB
1603 OPTIONAL_ Bayesian optimization of hyper-parameters.mp4 16.6 MB
1304 The wake-sleep algorithm.mp4 16.4 MB
1001 Why it helps to combine models.mp4 15.9 MB
0605 Rmsprop_ Divide the gradient by a running average of its recent magnitude.mp4 15.9 MB
0101 Why do we need machine learning_.mp4 15.8 MB
1002 Mixtures of Experts.mp4 15.7 MB
0602 A bag of tricks for mini-batch gradient descent.mp4 15.6 MB
1302 Belief Nets.mp4 15.6 MB
1101 Hopfield Nets.mp4 15.4 MB
0401 Learning to predict the next word.mp4 15.0 MB
0405 Ways to deal with the large number of possible outputs.mp4 14.9 MB
1303 Learning sigmoid belief nets.mp4 14.9 MB
1201 Boltzmann machine learning.mp4 14.7 MB
0803 Learning to predict the next character using HF.mp4 14.6 MB
1601 OPTIONAL_ Learning a joint model of images and captions.mp4 14.5 MB
0901 Overview of ways to improve generalization.mp4 14.2 MB
0301 Learning the weights of a linear neuron.mp4 14.2 MB
0304 The backpropagation algorithm.mp4 14.0 MB
1105 How a Boltzmann machine models data.mp4 13.9 MB
1102 Dealing with spurious minima.mp4 13.4 MB
1203 Restricted Boltzmann Machines.mp4 13.3 MB
0905 The Bayesian interpretation of weight decay.mp4 12.9 MB
0904 Introduction to the full Bayesian approach.mp4 12.6 MB
1301 The ups and downs of back propagation.mp4 12.4 MB
1104 Using stochastic units to improv search.mp4 12.3 MB
1505 Learning binary codes for image retrieval.mp4 12.1 MB
1103 Hopfield nets with hidden units.mp4 11.9 MB
1402 Discriminative learning for DBNs.mp4 11.8 MB
0804 Echo State Networks.mp4 11.8 MB
1404 Modeling real-valued data with an RBM.mp4 11.7 MB
1602 OPTIONAL_ Hierarchical Coordinate Frames.mp4 11.7 MB
0305 Using the derivatives computed by backpropagation.mp4 11.7 MB
1504 Semantic Hashing.mp4 11.5 MB
1503 Deep auto encoders for document retrieval.mp4 10.7 MB
0705 Long-term Short-term-memory.mp4 10.7 MB
1403 What happens during discriminative fine-tuning_.mp4 10.7 MB
0202 Perceptrons_ The first generation of neural networks.mp4 10.3 MB
0102 What are neural networks_.mp4 10.2 MB
0603 The momentum method.mp4 10.2 MB
1005 Dropout.mp4 10.2 MB
1501 From PCA to autoencoders.mp4 10.2 MB
0601 Overview of mini-batch gradient descent.mp4 10.1 MB
1205 RBMs for collaborative filtering.mp4 10.0 MB
0103 Some simple models of neurons.mp4 9.7 MB
0105 Three types of learning.mp4 9.4 MB
0404 Neuro-probabilistic language models.mp4 9.4 MB
0704 Why it is difficult to train an RNN.mp4 9.3 MB
0201 Types of neural network architectures.mp4 9.2 MB
1204 An example of RBM learning.mp4 9.1 MB
0903 Using noise as a regularizer.mp4 8.9 MB
1003 The idea of full Bayesian learning.mp4 8.8 MB
1506 Shallow autoencoders for pre-training.mp4 8.7 MB
1004 Making full Bayesian learning practical.mp4 8.5 MB
0403 Another diversion_ The softmax output function.mp4 8.4 MB
0902 Limiting the size of the weights.mp4 7.7 MB
0702 Training RNNs with back propagation.mp4 7.7 MB
0203 A geometrical view of perceptrons.mp4 7.7 MB
0703 A toy example of training an RNN.mp4 7.6 MB
0502 Achieving viewpoint invariance.mp4 7.2 MB
0604 Adaptive learning rates for each connection.mp4 7.0 MB
0104 A simple example of learning.mp4 6.9 MB
0204 Why the learning works.mp4 6.2 MB
0302 The error surface for a linear neuron.mp4 6.2 MB
0501 Why object recognition is difficult.mp4 5.6 MB
0402 A brief diversion into cognitive science.mp4 5.6 MB
1502 Deep auto encoders.mp4 5.2 MB
0906 MacKay_s quick and dirty method of setting weight costs.mp4 4.6 MB
0303 Learning the weights of a logistic output neuron.mp4 4.6 MB
Slides/lecture_slides-lec1.pdf 4.1 MB
Info/0304 reading_list-Learning representations by back-propagating errors.pdf 3.1 MB
1604 OPTIONAL_ The fog of progress.mp4 2.9 MB
Slides/lecture_slides-lec15.pdf 2.6 MB
Info/1303 reading_list-Connectionist learning of belief networks.pdf 2.4 MB
Slides/lecture_slides-lec12.pdf 1.8 MB
Info/1005 reading_list-Improving neural networks by preventing co-adaptation of feature detectors.pdf 1.7 MB
Slides/lecture_slides-lec5.pdf 1.6 MB
Slides/lecture_slides-lec14.pdf 1.2 MB
Slides/lecture_slides-lec7.pdf 976.0 kB
Slides/lecture_slides-lec4.pdf 964.1 kB
Info/0504 reading_list-Gradient-based learning applied to document recognition.pdf 955.1 kB
Slides/lecture_slides-lec10.pdf 847.1 kB
Info/1401 reading_list-A fast learning algorithm for deep belief nets.pdf 787.8 kB
Info/1505 reading_list-Using Very Deep Autoencoders for Content-Based Image Retrieval.pdf 759.2 kB
Slides/lecture_slides-lec9.pdf 719.0 kB
Slides/lecture_slides-lec11.pdf 711.2 kB
Slides/lecture_slides-lec8.pdf 658.3 kB
Info/1504 reading_list-Semantic Hashing.pdf 641.6 kB
Slides/lecture_slides-lec3.pdf 548.0 kB
Slides/lecture_slides-lec6.pdf 546.8 kB
Info/1401 reading_list-To recognize shapes, first learn to generate images.pdf 513.9 kB
Slides/lecture_slides-lec2.pdf 504.8 kB
Info/1401 reading_list-Self-taught learning- transfer learning from unlabeled data.pdf 484.9 kB
Slides/lecture_slides-lec16.pdf 346.9 kB
Info/0705 reading_list-A novel approach to on-line handwriting recognition based on bidirectional long short-term memory networks.pdf 320.6 kB
Info/0804 Echo state network - Scholarpedia.htm 318.9 kB
Slides/lecture_slides-lec13.pdf 314.6 kB
Info/1105 Boltzmann machine - Scholarpedia.htm 295.9 kB
Info/0803 reading_list-Generating Text with Recurrent Neural Networks.pdf 273.4 kB
Info/1002 reading_list-Adaptive mixtures of local experts.pdf 271.1 kB
Info/1304 reading_list-- algorithm for unsupervised neural networks.pdf 261.5 kB
Info/0405 images-Lecture4-turian.png 154.4 kB
Info/0804 Echo state network - Scholarpedia_files/load(1).php 154.2 kB
Info/1105 Boltzmann machine - Scholarpedia_files/load(1).php 154.2 kB
Info/0804 Echo state network - Scholarpedia_files/load(6).php 152.2 kB
Info/1105 Boltzmann machine - Scholarpedia_files/load(6).php 152.2 kB
Info/0404 reading_list-Neural probabilisic language models.pdf 140.1 kB
Info/0504 reading_list-Convolutional networks for images, speech, and time series.pdf 125.4 kB
Info/0804 Echo state network - Scholarpedia_files/cb=gapi.loaded_0 100.5 kB
Info/1105 Boltzmann machine - Scholarpedia_files/cb=gapi.loaded_0 100.5 kB
Info/0804 Echo state network - Scholarpedia_files/500px-FreqGenSchema.png 73.5 kB
Info/0804 Echo state network - Scholarpedia_files/load(4).php 68.1 kB
Info/1105 Boltzmann machine - Scholarpedia_files/load(4).php 68.1 kB
Info/0804 Echo state network - Scholarpedia_files/core-rpc-shindig.random-shindig.sha1.js 68.1 kB
Info/1105 Boltzmann machine - Scholarpedia_files/core-rpc-shindig.random-shindig.sha1.js 68.1 kB
Info/0804 Echo state network - Scholarpedia_files/MathJax.js 58.8 kB
Info/1105 Boltzmann machine - Scholarpedia_files/MathJax.js 58.8 kB
Info/0804 Echo state network - Scholarpedia_files/cb=gapi.loaded_1 51.4 kB
Info/1105 Boltzmann machine - Scholarpedia_files/cb=gapi.loaded_1 51.4 kB
Info/0804 Echo state network - Scholarpedia_files/fastbutton.htm 47.4 kB
Info/1105 Boltzmann machine - Scholarpedia_files/fastbutton.htm 47.4 kB
Info/0804 Echo state network - Scholarpedia_files/twitter.png 43.4 kB
Info/1105 Boltzmann machine - Scholarpedia_files/twitter.png 43.4 kB
Info/0804 Echo state network - Scholarpedia_files/ga.js 40.0 kB
Info/1105 Boltzmann machine - Scholarpedia_files/ga.js 40.0 kB
Info/0804 Echo state network - Scholarpedia_files/400px-FreqGenTestOverlay.png 39.9 kB
Info/0804 Echo state network - Scholarpedia_files/plusone.js 33.6 kB
Info/1105 Boltzmann machine - Scholarpedia_files/plusone.js 33.6 kB
0504 Convolutional nets for object recognition.srt 26.2 kB
1401 Learning layers of features by stacking RBMs.srt 23.4 kB
0701 Modeling sequences_ A brief overview.srt 23.2 kB
1405 OPTIONAL VIDEO_ RBMs are infinite sigmoid belief nets.srt 22.2 kB
0503 Convolutional nets for digit recognition.srt 22.1 kB
0602 A bag of tricks for mini-batch gradient descent.srt 19.2 kB
1603 OPTIONAL_ Bayesian optimization of hyper-parameters.srt 19.0 kB
0205 What perceptrons can_t do.srt 18.9 kB
0101 Why do we need machine learning_.srt 18.8 kB
1202 OPTIONAL VIDEO_ More efficient ways to get the statistics.srt 18.6 kB
0405 Ways to deal with the large number of possible outputs.srt 18.6 kB
0801 A brief overview of Hessian Free optimization.srt 18.4 kB
1001 Why it helps to combine models.srt 18.1 kB
0802 Modeling character strings with multiplicative connections.srt 17.9 kB
1304 The wake-sleep algorithm.srt 17.8 kB
1302 Belief Nets.srt 17.8 kB
1002 Mixtures of Experts.srt 17.5 kB
0401 Learning to predict the next word.srt 16.9 kB
1101 Hopfield Nets.srt 16.8 kB
1201 Boltzmann machine learning.srt 16.4 kB
1105 How a Boltzmann machine models data.srt 16.3 kB
0901 Overview of ways to improve generalization.srt 16.2 kB
0803 Learning to predict the next character using HF.srt 16.1 kB
0605 Rmsprop_ Divide the gradient by a running average of its recent magnitude.srt 16.1 kB
0301 Learning the weights of a linear neuron.srt 15.4 kB
0304 The backpropagation algorithm.srt 15.2 kB
1102 Dealing with spurious minima.srt 15.2 kB
1303 Learning sigmoid belief nets.srt 15.0 kB
1104 Using stochastic units to improv search.srt 14.3 kB
1301 The ups and downs of back propagation.srt 14.0 kB
1203 Restricted Boltzmann Machines.srt 13.9 kB
0305 Using the derivatives computed by backpropagation.srt 13.9 kB
1602 OPTIONAL_ Hierarchical Coordinate Frames.srt 13.7 kB
0904 Introduction to the full Bayesian approach.srt 13.5 kB
0905 The Bayesian interpretation of weight decay.srt 13.3 kB
1505 Learning binary codes for image retrieval.srt 13.2 kB
1402 Discriminative learning for DBNs.srt 13.0 kB
Info/1105 Boltzmann machine - Scholarpedia_files/postmessageRelay.htm 12.7 kB
Info/0804 Echo state network - Scholarpedia_files/postmessageRelay.htm 12.7 kB
Info/0804 Echo state network - Scholarpedia_files/load(5).php 12.7 kB
Info/1105 Boltzmann machine - Scholarpedia_files/load(5).php 12.7 kB
1103 Hopfield nets with hidden units.srt 12.6 kB
1404 Modeling real-valued data with an RBM.srt 12.4 kB
0804 Echo State Networks.srt 12.3 kB
0601 Overview of mini-batch gradient descent.srt 12.2 kB
1005 Dropout.srt 12.0 kB
0705 Long-term Short-term-memory.srt 11.9 kB
0102 What are neural networks_.srt 11.8 kB
1504 Semantic Hashing.srt 11.6 kB
0603 The momentum method.srt 11.4 kB
0202 Perceptrons_ The first generation of neural networks.srt 11.1 kB
0404 Neuro-probabilistic language models.srt 11.0 kB
0103 Some simple models of neurons.srt 11.0 kB
1205 RBMs for collaborative filtering.srt 10.9 kB
1403 What happens during discriminative fine-tuning_.srt 10.9 kB
1503 Deep auto encoders for document retrieval.srt 10.8 kB
0105 Three types of learning.srt 10.6 kB
1601 OPTIONAL_ Learning a joint model of images and captions.srt 10.6 kB
1003 The idea of full Bayesian learning.srt 10.5 kB
1501 From PCA to autoencoders.srt 10.5 kB
Info/0804 Echo state network - Scholarpedia_files/load.php 10.3 kB
Info/1105 Boltzmann machine - Scholarpedia_files/load.php 10.3 kB
1506 Shallow autoencoders for pre-training.srt 10.3 kB
1204 An example of RBM learning.srt 10.1 kB
0201 Types of neural network architectures.srt 10.1 kB
0704 Why it is difficult to train an RNN.srt 10.0 kB
0403 Another diversion_ The softmax output function.srt 9.3 kB
0903 Using noise as a regularizer.srt 9.1 kB
1004 Making full Bayesian learning practical.srt 8.7 kB
0902 Limiting the size of the weights.srt 8.6 kB
0702 Training RNNs with back propagation.srt 8.6 kB
0203 A geometrical view of perceptrons.srt 8.5 kB
0502 Achieving viewpoint invariance.srt 8.3 kB
0604 Adaptive learning rates for each connection.srt 7.9 kB
0703 A toy example of training an RNN.srt 7.7 kB
0104 A simple example of learning.srt 7.2 kB
0204 Why the learning works.srt 6.6 kB
0302 The error surface for a linear neuron.srt 6.5 kB
0501 Why object recognition is difficult.srt 6.3 kB
0402 A brief diversion into cognitive science.srt 5.9 kB
1502 Deep auto encoders.srt 5.5 kB
Info/0804 Echo state network - Scholarpedia_files/88x31.png 5.5 kB
Info/1105 Boltzmann machine - Scholarpedia_files/88x31.png 5.5 kB
Info/0804 Echo state network - Scholarpedia_files/1088796616-postmessagerelay.js 5.1 kB
Info/1105 Boltzmann machine - Scholarpedia_files/1088796616-postmessagerelay.js 5.1 kB
0303 Learning the weights of a logistic output neuron.srt 4.6 kB
0906 MacKay_s quick and dirty method of setting weight costs.srt 4.5 kB
Info/0804 Echo state network - Scholarpedia_files/badge.gif 3.7 kB
Info/1105 Boltzmann machine - Scholarpedia_files/badge.gif 3.7 kB
Info/0804 Echo state network - Scholarpedia_files/poweredby_mediawiki_88x31.png 3.6 kB
Info/1105 Boltzmann machine - Scholarpedia_files/poweredby_mediawiki_88x31.png 3.6 kB
1604 OPTIONAL_ The fog of progress.srt 3.6 kB
Info/0804 Echo state network - Scholarpedia_files/load(2).php 3.4 kB
Info/1105 Boltzmann machine - Scholarpedia_files/load(2).php 3.4 kB
Info/0804 Echo state network - Scholarpedia_files/linkedin.png 636 Bytes
Info/1105 Boltzmann machine - Scholarpedia_files/linkedin.png 636 Bytes
Info/0804 Echo state network - Scholarpedia_files/search-ltr.png 595 Bytes
Info/1105 Boltzmann machine - Scholarpedia_files/search-ltr.png 595 Bytes
Info/0804 Echo state network - Scholarpedia_files/facebook.png 540 Bytes
Info/1105 Boltzmann machine - Scholarpedia_files/facebook.png 540 Bytes
Info/0804 Echo state network - Scholarpedia_files/gplus-16.png 492 Bytes
Info/1105 Boltzmann machine - Scholarpedia_files/gplus-16.png 492 Bytes
Info/0804 Echo state network - Scholarpedia_files/load(3).php 428 Bytes
Info/1105 Boltzmann machine - Scholarpedia_files/load(3).php 428 Bytes
Info/0804 Echo state network - Scholarpedia_files/photo.jpg 356 Bytes
Info/1105 Boltzmann machine - Scholarpedia_files/photo.jpg 356 Bytes
Info/0804 Echo state network - Scholarpedia_files/magnify-clip.png 204 Bytes

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