Overfitting Computer Vision Input Layer Black Box Biases Feed Forward Hidden Layer Forward propagation Hidden Layer Back Propagation Gradient Descent Classification Step Function Supervised/Unsupervised Activation Function / Threshold Computer Vision Convolution / CNN Output Layer Input Layer Feed Forward Back propagation Initialization Weights Deep Learning Deep Learning Convolution (CNN) Forward Propagation Overfitting Step Function Node/ Weighted Sum Error/Cost Function Perceptron Sigmoid Function Activation Function/ Threshold Error/Cost Function Node/Weighted Sum Weights Recurrent (RNN) Recurrent / RNN Gradient Descent Output Layer Black Box (Interpretability) Sigmoid Function Supervised/ Unsupervised Initialization Biases Classification Perceptron Overfitting Computer Vision Input Layer Black Box Biases Feed Forward Hidden Layer Forward propagation Hidden Layer Back Propagation Gradient Descent Classification Step Function Supervised/Unsupervised Activation Function / Threshold Computer Vision Convolution / CNN Output Layer Input Layer Feed Forward Back propagation Initialization Weights Deep Learning Deep Learning Convolution (CNN) Forward Propagation Overfitting Step Function Node/ Weighted Sum Error/Cost Function Perceptron Sigmoid Function Activation Function/ Threshold Error/Cost Function Node/Weighted Sum Weights Recurrent (RNN) Recurrent / RNN Gradient Descent Output Layer Black Box (Interpretability) Sigmoid Function Supervised/ Unsupervised Initialization Biases Classification Perceptron
(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.
Overfitting
Computer Vision
Input Layer
Black Box
Biases
Feed Forward
Hidden Layer
Forward propagation
Hidden Layer
Back Propagation
Gradient Descent
Classification
Step Function
Supervised/Unsupervised
Activation Function / Threshold
Computer Vision
Convolution / CNN
Output Layer
Input Layer
Feed Forward
Back propagation
Initialization
Weights
Deep Learning
Deep Learning
Convolution (CNN)
Forward Propagation
Overfitting
Step Function
Node/
Weighted Sum
Error/Cost Function
Perceptron
Sigmoid Function
Activation Function/
Threshold
Error/Cost Function
Node/Weighted Sum
Weights
Recurrent
(RNN)
Recurrent / RNN
Gradient Descent
Output Layer
Black Box (Interpretability)
Sigmoid Function
Supervised/
Unsupervised
Initialization
Biases
Classification
Perceptron