Simple machine learning algorithms


1

184

May 24, 2019

Increasing accuracy, complexity and realworld impact


1

157

May 25, 2019

Goodfellow, Bengio, Courville  «Deep Learning» (2016)


2

561

May 24, 2019

Increasing model sizes


1

148

May 25, 2019

The number of neurons in animals and artificial neural networks


2

333

May 25, 2019

The number of connections per neuron in animals and artificial neural networks


2

319

May 25, 2019

The deep learning's history


1

277

May 25, 2019

Simple linear models: predecessors of modern deep learning


1

121

May 25, 2019

Increasing dataset sizes


1

330

May 25, 2019

The third wave of neural networks research


1

184

May 25, 2019

What is «connectionism»?


1

124

May 25, 2019

Deep neural networks in the mid1990s  mid2000s


1

139

May 25, 2019

What is «distributed representation»?


1

113

May 25, 2019

Why has the neuroscience's role in deep learning been diminished?


2

246

May 25, 2019

What is the «computational neuroscience»?


1

171

May 25, 2019

What has neuroscience given to deep learning?


2

258

May 25, 2019

Limitations of linear models


1

133

May 25, 2019

Historical trends in deep learning


1

137

May 24, 2019

Relationships between deep learning, representation learning, machine learning, and artificial intelligence


1

456

May 24, 2019

2 main ways of measuring the depth of a deep learning model


1

209

May 24, 2019

How does deep learning solve the central problem in representation learning?


1

229

May 24, 2019

What is a «feature»?


1

224

May 24, 2019

What is «disentangling factors of variation»?


1

122

May 24, 2019

What are «factors of variation»?


1

120

May 24, 2019

What is «representation learning»?


1

140

May 24, 2019

Сhoice of representation


1

124

May 24, 2019
