Neural Networks for Machine Learning 收录时间:2019-05-23 04:57:33 文件大小:920MB 下载次数:16 最近下载:2020-09-02 17:53:15 磁力链接: magnet:?xt=urn:btih:2d49241cf9a689583fe2352eab62ad3025a3e42f 立即下载 复制链接 文件列表 0504 Convolutional nets for object recognition.mp4 23MB 0701 Modeling sequences_ A brief overview.mp4 20MB 1401 Learning layers of features by stacking RBMs.mp4 20MB 1405 OPTIONAL VIDEO_ RBMs are infinite sigmoid belief nets.mp4 19MB 0503 Convolutional nets for digit recognition.mp4 18MB 1202 OPTIONAL VIDEO_ More efficient ways to get the statistics.mp4 17MB 0205 What perceptrons can_t do.mp4 17MB 0802 Modeling character strings with multiplicative connections.mp4 17MB 0801 A brief overview of Hessian Free optimization.mp4 16MB 1603 OPTIONAL_ Bayesian optimization of hyper-parameters.mp4 16MB 1304 The wake-sleep algorithm.mp4 16MB 1001 Why it helps to combine models.mp4 15MB 0605 Rmsprop_ Divide the gradient by a running average of its recent magnitude.mp4 15MB 0101 Why do we need machine learning_.mp4 15MB 1002 Mixtures of Experts.mp4 15MB 0602 A bag of tricks for mini-batch gradient descent.mp4 15MB 1302 Belief Nets.mp4 15MB 1101 Hopfield Nets.mp4 15MB 0401 Learning to predict the next word.mp4 14MB 0405 Ways to deal with the large number of possible outputs.mp4 14MB 1303 Learning sigmoid belief nets.mp4 14MB 1201 Boltzmann machine learning.mp4 14MB 0803 Learning to predict the next character using HF.mp4 14MB 1601 OPTIONAL_ Learning a joint model of images and captions.mp4 14MB 0901 Overview of ways to improve generalization.mp4 14MB 0301 Learning the weights of a linear neuron.mp4 14MB 0304 The backpropagation algorithm.mp4 13MB 1105 How a Boltzmann machine models data.mp4 13MB 1102 Dealing with spurious minima.mp4 13MB 1203 Restricted Boltzmann Machines.mp4 13MB 0905 The Bayesian interpretation of weight decay.mp4 12MB 0904 Introduction to the full Bayesian approach.mp4 12MB 1301 The ups and downs of back propagation.mp4 12MB 1104 Using stochastic units to improv search.mp4 12MB 1505 Learning binary codes for image retrieval.mp4 12MB 1103 Hopfield nets with hidden units.mp4 11MB 1402 Discriminative learning for DBNs.mp4 11MB 0804 Echo State Networks.mp4 11MB 1404 Modeling real-valued data with an RBM.mp4 11MB 1602 OPTIONAL_ Hierarchical Coordinate Frames.mp4 11MB 0305 Using the derivatives computed by backpropagation.mp4 11MB 1504 Semantic Hashing.mp4 11MB 1503 Deep auto encoders for document retrieval.mp4 10MB 0705 Long-term Short-term-memory.mp4 10MB 1403 What happens during discriminative fine-tuning_.mp4 10MB 0202 Perceptrons_ The first generation of neural networks.mp4 10MB 0102 What are neural networks_.mp4 10MB 0603 The momentum method.mp4 10MB 1005 Dropout.mp4 10MB 1501 From PCA to autoencoders.mp4 10MB 0601 Overview of mini-batch gradient descent.mp4 10MB 1205 RBMs for collaborative filtering.mp4 10MB 0103 Some simple models of neurons.mp4 9MB 0105 Three types of learning.mp4 9MB 0404 Neuro-probabilistic language models.mp4 9MB 0704 Why it is difficult to train an RNN.mp4 9MB 0201 Types of neural network architectures.mp4 9MB 1204 An example of RBM learning.mp4 9MB 0903 Using noise as a regularizer.mp4 8MB 1003 The idea of full Bayesian learning.mp4 8MB 1506 Shallow autoencoders for pre-training.mp4 8MB 1004 Making full Bayesian learning practical.mp4 8MB 0403 Another diversion_ The softmax output function.mp4 8MB 0902 Limiting the size of the weights.mp4 7MB 0702 Training RNNs with back propagation.mp4 7MB 0203 A geometrical view of perceptrons.mp4 7MB 0703 A toy example of training an RNN.mp4 7MB 0502 Achieving viewpoint invariance.mp4 7MB 0604 Adaptive learning rates for each connection.mp4 7MB 0104 A simple example of learning.mp4 7MB 0204 Why the learning works.mp4 6MB 0302 The error surface for a linear neuron.mp4 6MB 0501 Why object recognition is difficult.mp4 5MB 0402 A brief diversion into cognitive science.mp4 5MB 1502 Deep auto encoders.mp4 5MB 0906 MacKay_s quick and dirty method of setting weight costs.mp4 4MB 0303 Learning the weights of a logistic output neuron.mp4 4MB Slides/lecture_slides-lec1.pdf 4MB Info/0304 reading_list-Learning representations by back-propagating errors.pdf 3MB 1604 OPTIONAL_ The fog of progress.mp4 3MB Slides/lecture_slides-lec15.pdf 2MB Info/1303 reading_list-Connectionist learning of belief networks.pdf 2MB Slides/lecture_slides-lec12.pdf 2MB Info/1005 reading_list-Improving neural networks by preventing co-adaptation of feature detectors.pdf 2MB Slides/lecture_slides-lec5.pdf 2MB Slides/lecture_slides-lec14.pdf 1MB Slides/lecture_slides-lec7.pdf 953KB Slides/lecture_slides-lec4.pdf 941KB Info/0504 reading_list-Gradient-based learning applied to document recognition.pdf 933KB Slides/lecture_slides-lec10.pdf 827KB Info/1401 reading_list-A fast learning algorithm for deep belief nets.pdf 769KB Info/1505 reading_list-Using Very Deep Autoencoders for Content-Based Image Retrieval.pdf 741KB Slides/lecture_slides-lec9.pdf 702KB Slides/lecture_slides-lec11.pdf 695KB Slides/lecture_slides-lec8.pdf 643KB Info/1504 reading_list-Semantic Hashing.pdf 627KB Slides/lecture_slides-lec3.pdf 535KB Slides/lecture_slides-lec6.pdf 534KB Info/1401 reading_list-To recognize shapes, first learn to generate images.pdf 502KB Slides/lecture_slides-lec2.pdf 493KB Info/1401 reading_list-Self-taught learning- transfer learning from unlabeled data.pdf 474KB Slides/lecture_slides-lec16.pdf 339KB Info/0705 reading_list-A novel approach to on-line handwriting recognition based on bidirectional long short-term memory networks.pdf 313KB Info/0804 Echo state network - Scholarpedia.htm 311KB Slides/lecture_slides-lec13.pdf 307KB Info/1105 Boltzmann machine - Scholarpedia.htm 289KB Info/0803 reading_list-Generating Text with Recurrent Neural Networks.pdf 267KB Info/1002 reading_list-Adaptive mixtures of local experts.pdf 265KB Info/1304 reading_list-- algorithm for unsupervised neural networks.pdf 255KB Info/0405 images-Lecture4-turian.png 151KB Info/0804 Echo state network - Scholarpedia_files/load(1).php 151KB Info/1105 Boltzmann machine - Scholarpedia_files/load(1).php 151KB Info/0804 Echo state network - Scholarpedia_files/load(6).php 149KB Info/1105 Boltzmann machine - Scholarpedia_files/load(6).php 149KB Info/0404 reading_list-Neural probabilisic language models.pdf 137KB Info/0504 reading_list-Convolutional networks for images, speech, and time series.pdf 122KB Info/0804 Echo state network - Scholarpedia_files/cb=gapi.loaded_0 98KB Info/1105 Boltzmann machine - Scholarpedia_files/cb=gapi.loaded_0 98KB Info/0804 Echo state network - Scholarpedia_files/500px-FreqGenSchema.png 72KB Info/0804 Echo state network - Scholarpedia_files/load(4).php 67KB Info/1105 Boltzmann machine - Scholarpedia_files/load(4).php 67KB Info/0804 Echo state network - Scholarpedia_files/core-rpc-shindig.random-shindig.sha1.js 66KB Info/1105 Boltzmann machine - Scholarpedia_files/core-rpc-shindig.random-shindig.sha1.js 66KB Info/0804 Echo state network - Scholarpedia_files/MathJax.js 57KB Info/1105 Boltzmann machine - Scholarpedia_files/MathJax.js 57KB Info/0804 Echo state network - Scholarpedia_files/cb=gapi.loaded_1 50KB Info/1105 Boltzmann machine - Scholarpedia_files/cb=gapi.loaded_1 50KB Info/0804 Echo state network - Scholarpedia_files/fastbutton.htm 46KB Info/1105 Boltzmann machine - Scholarpedia_files/fastbutton.htm 46KB Info/0804 Echo state network - Scholarpedia_files/twitter.png 42KB Info/1105 Boltzmann machine - Scholarpedia_files/twitter.png 42KB Info/0804 Echo state network - Scholarpedia_files/ga.js 39KB Info/1105 Boltzmann machine - Scholarpedia_files/ga.js 39KB Info/0804 Echo state network - Scholarpedia_files/400px-FreqGenTestOverlay.png 39KB Info/0804 Echo state network - Scholarpedia_files/plusone.js 33KB Info/1105 Boltzmann machine - Scholarpedia_files/plusone.js 33KB 0504 Convolutional nets for object recognition.srt 26KB 1401 Learning layers of features by stacking RBMs.srt 23KB 0701 Modeling sequences_ A brief overview.srt 23KB 1405 OPTIONAL VIDEO_ RBMs are infinite sigmoid belief nets.srt 22KB 0503 Convolutional nets for digit recognition.srt 22KB 0602 A bag of tricks for mini-batch gradient descent.srt 19KB 1603 OPTIONAL_ Bayesian optimization of hyper-parameters.srt 19KB 0205 What perceptrons can_t do.srt 19KB 0101 Why do we need machine learning_.srt 18KB 1202 OPTIONAL VIDEO_ More efficient ways to get the statistics.srt 18KB 0405 Ways to deal with the large number of possible outputs.srt 18KB 0801 A brief overview of Hessian Free optimization.srt 18KB 1001 Why it helps to combine models.srt 18KB 0802 Modeling character strings with multiplicative connections.srt 17KB 1304 The wake-sleep algorithm.srt 17KB 1302 Belief Nets.srt 17KB 1002 Mixtures of Experts.srt 17KB 0401 Learning to predict the next word.srt 16KB 1101 Hopfield Nets.srt 16KB 1201 Boltzmann machine learning.srt 16KB 1105 How a Boltzmann machine models data.srt 16KB 0901 Overview of ways to improve generalization.srt 16KB 0803 Learning to predict the next character using HF.srt 16KB 0605 Rmsprop_ Divide the gradient by a running average of its recent magnitude.srt 16KB 0301 Learning the weights of a linear neuron.srt 15KB 0304 The backpropagation algorithm.srt 15KB 1102 Dealing with spurious minima.srt 15KB 1303 Learning sigmoid belief nets.srt 15KB 1104 Using stochastic units to improv search.srt 14KB 1301 The ups and downs of back propagation.srt 14KB 1203 Restricted Boltzmann Machines.srt 14KB 0305 Using the derivatives computed by backpropagation.srt 14KB 1602 OPTIONAL_ Hierarchical Coordinate Frames.srt 13KB 0904 Introduction to the full Bayesian approach.srt 13KB 0905 The Bayesian interpretation of weight decay.srt 13KB 1505 Learning binary codes for image retrieval.srt 13KB 1402 Discriminative learning for DBNs.srt 13KB Info/1105 Boltzmann machine - Scholarpedia_files/postmessageRelay.htm 12KB Info/0804 Echo state network - Scholarpedia_files/postmessageRelay.htm 12KB Info/0804 Echo state network - Scholarpedia_files/load(5).php 12KB Info/1105 Boltzmann machine - Scholarpedia_files/load(5).php 12KB 1103 Hopfield nets with hidden units.srt 12KB 1404 Modeling real-valued data with an RBM.srt 12KB 0804 Echo State Networks.srt 12KB 0601 Overview of mini-batch gradient descent.srt 12KB 1005 Dropout.srt 12KB 0705 Long-term Short-term-memory.srt 12KB 0102 What are neural networks_.srt 12KB 1504 Semantic Hashing.srt 11KB 0603 The momentum method.srt 11KB 0202 Perceptrons_ The first generation of neural networks.srt 11KB 0404 Neuro-probabilistic language models.srt 11KB 0103 Some simple models of neurons.srt 11KB 1205 RBMs for collaborative filtering.srt 11KB 1403 What happens during discriminative fine-tuning_.srt 11KB 1503 Deep auto encoders for document retrieval.srt 11KB 0105 Three types of learning.srt 10KB 1601 OPTIONAL_ Learning a joint model of images and captions.srt 10KB 1003 The idea of full Bayesian learning.srt 10KB 1501 From PCA to autoencoders.srt 10KB Info/0804 Echo state network - Scholarpedia_files/load.php 10KB Info/1105 Boltzmann machine - Scholarpedia_files/load.php 10KB 1506 Shallow autoencoders for pre-training.srt 10KB 1204 An example of RBM learning.srt 10KB 0201 Types of neural network architectures.srt 10KB 0704 Why it is difficult to train an RNN.srt 10KB 0403 Another diversion_ The softmax output function.srt 9KB 0903 Using noise as a regularizer.srt 9KB 1004 Making full Bayesian learning practical.srt 8KB 0902 Limiting the size of the weights.srt 8KB 0702 Training RNNs with back propagation.srt 8KB 0203 A geometrical view of perceptrons.srt 8KB 0502 Achieving viewpoint invariance.srt 8KB 0604 Adaptive learning rates for each connection.srt 8KB 0703 A toy example of training an RNN.srt 8KB 0104 A simple example of learning.srt 7KB 0204 Why the learning works.srt 6KB 0302 The error surface for a linear neuron.srt 6KB 0501 Why object recognition is difficult.srt 6KB 0402 A brief diversion into cognitive science.srt 6KB 1502 Deep auto encoders.srt 5KB Info/0804 Echo state network - Scholarpedia_files/88x31.png 5KB Info/1105 Boltzmann machine - Scholarpedia_files/88x31.png 5KB Info/0804 Echo state network - Scholarpedia_files/1088796616-postmessagerelay.js 5KB Info/1105 Boltzmann machine - Scholarpedia_files/1088796616-postmessagerelay.js 5KB 0303 Learning the weights of a logistic output neuron.srt 4KB 0906 MacKay_s quick and dirty method of setting weight costs.srt 4KB Info/0804 Echo state network - Scholarpedia_files/badge.gif 4KB Info/1105 Boltzmann machine - Scholarpedia_files/badge.gif 4KB Info/0804 Echo state network - Scholarpedia_files/poweredby_mediawiki_88x31.png 4KB Info/1105 Boltzmann machine - Scholarpedia_files/poweredby_mediawiki_88x31.png 4KB 1604 OPTIONAL_ The fog of progress.srt 3KB Info/0804 Echo state network - Scholarpedia_files/load(2).php 3KB Info/1105 Boltzmann machine - Scholarpedia_files/load(2).php 3KB Info/0804 Echo state network - 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