Search for tag: "deep learning"

Dropout 1: Definitions

Let's define the dropout algorithm (Google Drive).

From  Richard Sowers 216 plays 0  

Recurrent Neural Networks 3: Long Short Term Memory networks

Let's understand Long Short Term Memory (LSTM) networks (Google Drive)

From  Richard Sowers 112 plays 0  

Recurrent Neural Networks 1: The Plant-Observer paradigm

Let's understand Recurrent Neural Networks via the plant observer architecture from systems theory (Google Drive)

From  Richard Sowers 231 plays 0  

Recurrent Neural Networks 2: Basic RNN's

Let's understand some basic architectures of Recurrent Neural Networks and their properties (Google Drive)

From  Richard Sowers 218 plays 0  

ISE Information Day: Data Analytics

This video contains a brief description of the Department of Industrial & Enterprise Systems Engineering's undergraduate majors and student opportunities by Associate Director Heidi Craddock…

From  Heidi Craddock 16 plays 0  

Feed Forward Neural Networks 4: Quadrants 1 and 3 (3 layers)

Let's look at a 3-layer neural network which identifies quadrants 1 and 3 in the plane (Google Drive).

From  Richard Sowers 127 plays 0  

Feed Forward Neural Networks 3: Quadrants 1 and 3 (2 layers)

Let's look at a 2-layer neural network which identifies quadrants 1 and 3 in the plane (Google Drive).

From  Richard Sowers 110 plays 0  

Feed Forward Neural Networks 2: Quadrant 1

Let's look at a 2-layer neural network which identifies quadrant 1 in the plane (Google Drive).

From  Richard Sowers 129 plays 0  

Feed Forward Neural Networks 1: Quadrants 1 and 4

Let's look at a 2-layer neural network which identifies quadrants 1 and 4 in the plane (Google Drive).

From  Richard Sowers 267 plays 0  

Stochastic Gradient Descent 4: Batch Sizes

Let's understand a bit about batch sizes (Google Drive)

From  Richard Sowers 78 plays 0  

Stochastic Gradient Descent 3: Proofs (part 2)

Let's understand some proofs of stochastic gradient descent (part 2) (Google Drive)

From  Richard Sowers 90 plays 0  

Stochastic Gradient Descent 2: Proofs (part 1)

Let's understand some proofs of stochastic gradient descent (part 1) (Google Drive)

From  Richard Sowers 104 plays 0  

Stochastic Gradient Descent 1: structure

Let's define stochastic gradient descent (Google Drive)

From  Richard Sowers 197 plays 0  

Stochastic Gradient Descent 5: Epochs

Let's consider the notion of an epoch (Google Drive)

From  Richard Sowers 73 plays 0  

Training Validation and Testing 2: K-fold CrossValidation

Let's understand cross-validation (Google Drive)

From  Richard Sowers 124 plays 0  

Training Testing and Validation 1: models

Let's look at Training, Testing, and Validation (Google Drive)

From  Richard Sowers 214 plays 0  

TruthTables 2: Layers

Let's write out matrix representations of approximations of truth tables in a common way (Google Drive)

From  Richard Sowers 333 plays 0  

Truth Tables 1: Sigmoid functions

Let's represent 2-dimensional truth tables as combinations of squeezed sigmoids (Google Drive)

From  Richard Sowers 576 plays 0  

Backpropagation 3: Vector calculations

Let's finally consider multidimensional backpropagation (Google Drive)

From  Richard Sowers 219 plays 0  

Backpropagation 2: Affine maps

Let's next include additive parameters (Google Drive)

From  Richard Sowers 202 plays 0  

Backpropagation 1: Multiplicative parameters

Let's understand backpropagation with multiplicative parameters (Google Drive)

From  Richard Sowers 400 plays 0  

Linear Regression 3: Gradient Descent

Let's write out the exact solution of Linear Regression (Google Drive)

From  Richard Sowers 268 plays 0  

Logistic Regression 4: Regularization

Let's understand how to regularize logistic regression (Google Drive)

From  Richard Sowers 167 plays 0  

Logistic Regression 3: Scaling and Solution

Let's rescale and iteratively solve logistic regression (Google Drive)

From  Richard Sowers 229 plays 0