Optimizing and Training Recurrent Networks

  • 33 views
  • 1 hour, 10 minutes, 35 seconds
  • Uploaded by Deep Learning

Related videos

64:32
Свёрточные сети и их приложения к компьютерному зрению Deep Learning
66:18
GPU и глубокое обучение Deep Learning
96:56
ЕМ-алгоритм и его обобщения в задачах обучения с неполной информацией Deep Learning
50:37
Введение в проблематику построения систем анализа больших данных – мировых научных публикаций и патентов Deep Learning
90:06
Deep Learning: a Revolution in Artificial Intelligence Deep Learning
101:30
Why Deep Learning? Deep Learning
62:49
Multilayered Networks and Gradient-based Backpropagation Deep Learning
64:22
Deep Learning in Practice Deep Learning
58:57
Convolutional Neural Networks Deep Learning
24:07
Convolutional Networks and their Applications in Vision Deep Learning
54:19
Recurrent Neural Networks and their Applications in Natural Language Processing Deep Learning
61:01
Reasoning, Attention, Memory Deep Learning
106:55
Unsupervised Learning Deep Learning
45:57
The Mathematical Mysteries behind Convolutional Neural Networks Deep Learning
47:54
Speech Recognition Deep Learning
85:32
Metric Learning for Structured Predictions Deep Learning
65:03
Translating and Natural Language Processing Deep Learning
61:10
Deep Learning and Reasoning, Memory-Augmented Networks Deep Learning
75:17
CS224D Lecture 1 - 29th Mar 2016 Deep Learning
78:13
CS224D Lecture 2 - 31st Mar 2016 Deep Learning
77:56
CS224D Lecture 3 - 5th Apr 2016 Deep Learning
77:42
CS224D Lecture 4 - 7th Apr 2016 Deep Learning
79:06
CS224D Lecture 5 - 12th Apr 2016 Deep Learning
78:28
CS224D Lecture 6 - 14th Apr 2016 Deep Learning
79:46
CS224D Lecture 7 - Introduction to TensorFlow (19th Apr 2016 Deep Learning
81:10
CS224D Lecture 8 - 21st Apr 2016 Deep Learning
78:44
CS224D Lecture 10 - 28th Apr 2016 Deep Learning
81:12
CS224D Lecture 11 - 3rd May 2016 Deep Learning
9:31
AWS Tutorial Deep Learning
13:14
Lecture 1-1. Why do we need Machine Learning? Deep Learning
8:30
Lecture 1-2. What are Neural Networks? Deep Learning
8:23
Lecture 1-3. Some simple models of neurons Deep Learning
5:38
Lecture 1-4. A simple example of learning Deep Learning
7:37
Lecture 1-5. Three types of learning Deep Learning
7:28
Lecture 2-1. Types of neural network architectures Deep Learning
8:16
Lecture 2-2. Perceptions: The first generation of neural networks Deep Learning
6:24
Lecture 2-3. A geometrical view of perceptrons Deep Learning
5:09
Lecture 2-4. Why the learning works Deep Learning
14:34
Lecture 2-5. Whar perceptrons can't do Deep Learning
11:54
Lecture 3-1. Learning the weights of a linear neuron Deep Learning
5:02
Lecture 3-2. The error surface for a linear neuron Deep Learning
3:56
Lecture 3-3. Learning the weights of a logistic output neuron Deep Learning
11:50
Lecture 3-4. The backpropagation algorithm Deep Learning
9:49
Lecture 3-5. Using the derivatives computed by backpropagation Deep Learning
12:33
Lecture 4-1. Learning to predict the next word Deep Learning
4:26
Lecture 4-2. A brief diversion into cognitive science Deep Learning
7:20
Lecture 4-3. Another diversion: The softmax output function Deep Learning
7:52
Lecture 4-4. Neuro-probabilistic language models Deep Learning

Deep Learning at Collège de France (Yann LeCun)

You might be interested

втроём писсинг
Видео от ko mg
черный член тренинг
филипинку
啤酒瓶
Twerk PAWG booty teen pmv compilation