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Neural Networks for Machine Learning
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65ec8a88b2c48329bd11761a87f0eef0bfca60ed
文档大小:
964.3 MB
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243
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收录时间:
2020-01-30
最近下载:
2025-01-24
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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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