Search for tag: "deep learning"

Dropout 1: Definitions

Let's understand Dropout (Google Drive).

From  Richard Sowers 349 plays 0  

Recurrent Neural Networks 3: More Complex Networks

Let's understand Recurrent Neural Networks (Google Drive)

From  Richard Sowers 126 plays 0  

Recurrent Neural Networks 1: The Plant-Observer paradigm

Let's understand Recurrent Neural Networks (Google Drive)

From  Richard Sowers 258 plays 0  

Recurrent Neural Networks 2: Basic RNN's

Let's understand Recurrent Neural Networks (Google Drive)

From  Richard Sowers 228 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 18 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 193 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 160 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 201 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 445 plays 0  

Gradient Descent 4: Stochastic Gradient Descent

Let's consider gradient descent (Google Drive)

From  Richard Sowers 125 plays 0  

Gradient Descent 3: Stopping

Let's consider gradient descent (Google Drive)

From  Richard Sowers 141 plays 0  

Gradient Descent 2: Convergence

Let's consider gradient descent (Google Drive)

From  Richard Sowers 174 plays 0  

Gradient Descent 1: Structure

Let's consider gradient descent (Google Drive)

From  Richard Sowers 335 plays 0  

Gradient Descent 5: Learning Schedules

Let's consider gradient descent (Google Drive)

From  Richard Sowers 123 plays 0  

Training Validation and Testing 2: K-fold CrossValidation

Let's understand cross-validation (Google Drive)

From  Richard Sowers 182 plays 0  

Training Testing and Validation 1: models

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

From  Richard Sowers 305 plays 0  

Truth Tables 2: Layers

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

From  Richard Sowers 490 plays 0  

Truth Tables 1: Sigmoid functions

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

From  Richard Sowers 805 plays 0  

Backpropagation 3: Vector calculations

Let's finally consider multidimensional backpropagation (Google Drive)

From  Richard Sowers 286 plays 0  

Backpropagation 2: Affine maps

Let's next include additive parameters (Google Drive)

From  Richard Sowers 275 plays 0  

Backpropagation 1: Multiplicative parameters

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

From  Richard Sowers 568 plays 0  

Linear Regression 4: Computational Linear Algebra

Let's think a bit about how linear algebra is implemented (Google Drive)

From  Richard Sowers 362 plays 0  

Linear Regression 3: Gradient Descent

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

From  Richard Sowers 449 plays 0  

Logistic Regression 4: Regularization

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

From  Richard Sowers 230 plays 0