Convolution(CNN)WeightsDeepLearningInputLayerBiasesSupervised/UnsupervisedError/CostFunctionStepFunctionNode/WeightedSumSigmoidFunctionBlackBoxComputerVisionPerceptronHiddenLayerRecurrent(RNN)OutputLayerActivationFunction/ThresholdBiasesSigmoidFunctionFeedForwardDeepLearningInitializationClassificationActivationFunction /ThresholdInitializationRecurrent/ RNNSupervised/UnsupervisedError/CostFunctionWeightsForwardpropagationInputLayerHiddenLayerOverfittingComputerVisionBackpropagationOutputLayerConvolution/ CNNBackPropagationForwardPropagationOverfittingFeedForwardStepFunctionPerceptronGradientDescentNode/WeightedSumGradientDescentBlack Box(Interpretability)ClassificationConvolution(CNN)WeightsDeepLearningInputLayerBiasesSupervised/UnsupervisedError/CostFunctionStepFunctionNode/WeightedSumSigmoidFunctionBlackBoxComputerVisionPerceptronHiddenLayerRecurrent(RNN)OutputLayerActivationFunction/ThresholdBiasesSigmoidFunctionFeedForwardDeepLearningInitializationClassificationActivationFunction /ThresholdInitializationRecurrent/ RNNSupervised/UnsupervisedError/CostFunctionWeightsForwardpropagationInputLayerHiddenLayerOverfittingComputerVisionBackpropagationOutputLayerConvolution/ CNNBackPropagationForwardPropagationOverfittingFeedForwardStepFunctionPerceptronGradientDescentNode/WeightedSumGradientDescentBlack Box(Interpretability)Classification

Neural Network Keyword Bingo - Call List

(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.


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  1. Convolution (CNN)
  2. Weights
  3. Deep Learning
  4. Input Layer
  5. Biases
  6. Supervised/Unsupervised
  7. Error/Cost Function
  8. Step Function
  9. Node/ Weighted Sum
  10. Sigmoid Function
  11. Black Box
  12. Computer Vision
  13. Perceptron
  14. Hidden Layer
  15. Recurrent (RNN)
  16. Output Layer
  17. Activation Function/ Threshold
  18. Biases
  19. Sigmoid Function
  20. Feed Forward
  21. Deep Learning
  22. Initialization
  23. Classification
  24. Activation Function / Threshold
  25. Initialization
  26. Recurrent / RNN
  27. Supervised/ Unsupervised
  28. Error/Cost Function
  29. Weights
  30. Forward propagation
  31. Input Layer
  32. Hidden Layer
  33. Overfitting
  34. Computer Vision
  35. Back propagation
  36. Output Layer
  37. Convolution / CNN
  38. Back Propagation
  39. Forward Propagation
  40. Overfitting
  41. Feed Forward
  42. Step Function
  43. Perceptron
  44. Gradient Descent
  45. Node/Weighted Sum
  46. Gradient Descent
  47. Black Box (Interpretability)
  48. Classification