Forward Propagation Gradient Descent Black Box (Interpretability) Deep Learning Node/ Weighted Sum Sigmoid Function Overfitting Input Layer Node/Weighted Sum Back propagation Feed Forward Error/Cost Function Perceptron Gradient Descent Convolution (CNN) Forward propagation Recurrent (RNN) Feed Forward Supervised/Unsupervised Activation Function / Threshold Computer Vision Step Function Hidden Layer Output Layer Input Layer Perceptron Initialization Biases Error/Cost Function Hidden Layer Black Box Step Function Initialization Convolution / CNN Overfitting Computer Vision Sigmoid Function Weights Classification Activation Function/ Threshold Recurrent / RNN Biases Deep Learning Output Layer Classification Weights Back Propagation Supervised/ Unsupervised Forward Propagation Gradient Descent Black Box (Interpretability) Deep Learning Node/ Weighted Sum Sigmoid Function Overfitting Input Layer Node/Weighted Sum Back propagation Feed Forward Error/Cost Function Perceptron Gradient Descent Convolution (CNN) Forward propagation Recurrent (RNN) Feed Forward Supervised/Unsupervised Activation Function / Threshold Computer Vision Step Function Hidden Layer Output Layer Input Layer Perceptron Initialization Biases Error/Cost Function Hidden Layer Black Box Step Function Initialization Convolution / CNN Overfitting Computer Vision Sigmoid Function Weights Classification Activation Function/ Threshold Recurrent / RNN Biases Deep Learning Output Layer Classification Weights Back Propagation Supervised/ Unsupervised
(Print) Use this randomly generated list as your call list when playing the game. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.
Forward Propagation
Gradient Descent
Black Box (Interpretability)
Deep Learning
Node/
Weighted Sum
Sigmoid Function
Overfitting
Input Layer
Node/Weighted Sum
Back propagation
Feed Forward
Error/Cost Function
Perceptron
Gradient Descent
Convolution (CNN)
Forward propagation
Recurrent
(RNN)
Feed Forward
Supervised/Unsupervised
Activation Function / Threshold
Computer Vision
Step Function
Hidden Layer
Output Layer
Input Layer
Perceptron
Initialization
Biases
Error/Cost Function
Hidden Layer
Black Box
Step Function
Initialization
Convolution / CNN
Overfitting
Computer Vision
Sigmoid Function
Weights
Classification
Activation Function/
Threshold
Recurrent / RNN
Biases
Deep Learning
Output Layer
Classification
Weights
Back Propagation
Supervised/
Unsupervised