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Featured video

K-means clustering: how it works

Victor Lavrenko

860,593 views

11 years ago

Neural Networks and Backpropagation
Victor Lavrenko
Neural Networks 1: a 3-minute history
00:03:33
Neural Networks 1: a 3-minute history

33,279 views

9 years ago

Victor Lavrenko
Neural Networks 2: machine learning = feature engineering
00:04:59
Neural Networks 2: machine learning = feature engineering

33,217 views

9 years ago

Victor Lavrenko
Neural Networks 3: axons, dendrites, synapses
00:03:23
Neural Networks 3: axons, dendrites, synapses

29,631 views

9 years ago

Victor Lavrenko
Neural Networks 4: McCulloch & Pitts neuron
00:03:29
Neural Networks 4: McCulloch & Pitts neuron

38,803 views

9 years ago

Victor Lavrenko
Neural Networks 5: feedforward, recurrent and RBM
00:04:56
Neural Networks 5: feedforward, recurrent and RBM

45,350 views

9 years ago

Victor Lavrenko
Neural Networks 6: solving XOR with a hidden layer
00:05:53
Neural Networks 6: solving XOR with a hidden layer

251,522 views

9 years ago

Victor Lavrenko
Neural Networks 7: universal approximation
00:02:29
Neural Networks 7: universal approximation

27,394 views

9 years ago

Victor Lavrenko
Neural Networks 8: hidden units = features
00:05:45
Neural Networks 8: hidden units = features

22,151 views

9 years ago

Victor Lavrenko
Neural Networks 9: derivatives we need for backprop
00:03:08
Neural Networks 9: derivatives we need for backprop

17,120 views

9 years ago

Victor Lavrenko
Backpropagation: how it works
00:06:08
Backpropagation: how it works

151,102 views

9 years ago

Victor Lavrenko
Neural Networks 11: Backpropagation in detail
00:05:13
Neural Networks 11: Backpropagation in detail

22,806 views

9 years ago

Victor Lavrenko
Neural Networks 12: multiclass classification
00:01:09
Neural Networks 12: multiclass classification

13,797 views

9 years ago

IR20 Machine Learning for IR
Victor Lavrenko
IR20.1 Centroid classifier
00:06:16
IR20.1 Centroid classifier

15,592 views

9 years ago

Victor Lavrenko
IR20.2 Large margin classification
00:06:01
IR20.2 Large margin classification

5,966 views

9 years ago

Victor Lavrenko
IR20.3 Passive-aggressive algorithm (PA)
00:13:16
IR20.3 Passive-aggressive algorithm (PA)

10,292 views

9 years ago

Victor Lavrenko
IR20.4 Convergence of the PA algorithm
00:06:47
IR20.4 Convergence of the PA algorithm

3,255 views

9 years ago

Victor Lavrenko
IR20.5 SVM explained visually
00:10:01
IR20.5 SVM explained visually

11,126 views

9 years ago

Victor Lavrenko
IR20.6 Sequential minimal optimization (SMO)
00:08:54
IR20.6 Sequential minimal optimization (SMO)

16,762 views

9 years ago

Victor Lavrenko
IR20.7 Learning to rank for Information Retrieval
00:04:24
IR20.7 Learning to rank for Information Retrieval

6,950 views

9 years ago

Victor Lavrenko
IR20.8 Learning to rank with an SVM
00:02:32
IR20.8 Learning to rank with an SVM

10,492 views

9 years ago

Victor Lavrenko
IR20.9 Learning to rank: features
00:01:11
IR20.9 Learning to rank: features

3,591 views

9 years ago

Victor Lavrenko
IR20.10 Learning to rank with click data
00:05:41
IR20.10 Learning to rank with click data

6,500 views

9 years ago

Victor Lavrenko
IR20.11 Summary
00:01:03
IR20.11 Summary

2,009 views

9 years ago

Popular videos
Victor Lavrenko
K-means clustering: how it works
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Decision Tree 1: how it works
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Decision Tree 1: how it works

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EM algorithm: how it works
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EM algorithm: how it works

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Expectation Maximization: how it works
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Neural Networks 6: solving XOR with a hidden layer
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Decision Tree 3: which attribute to split on?
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Decision Tree 3: which attribute to split on?

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Victor Lavrenko
Decision Tree 4: Information Gain
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Decision Tree 4: Information Gain

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Victor Lavrenko
ID3 algorithm: how it works
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KD tree algorithm: how it works
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Agglomerative Clustering: how it works
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Agglomerative Clustering: how it works

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Decision Tree 5: overfitting and pruning
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Decision Tree 5: overfitting and pruning

152,966 views

11 years ago

Victor Lavrenko
Backpropagation: how it works
00:06:08
Backpropagation: how it works

151,102 views

9 years ago

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Introductory Applied Machine Learning (IAML)

Text Technologies for Data Science (TTS)