ComputerVisionWeightsNode/WeightedSumBiasesNode/WeightedSumFeedForwardFeedForwardForwardPropagationClassificationInitializationError/CostFunctionSupervised/UnsupervisedConvolution/ CNNHiddenLayerBiasesBackPropagationStepFunctionActivationFunction/ThresholdDeepLearningSupervised/UnsupervisedClassificationBackpropagationInputLayerDeepLearningBlack Box(Interpretability)BlackBoxOverfittingComputerVisionWeightsSigmoidFunctionRecurrent(RNN)Recurrent/ RNNGradientDescentError/CostFunctionOutputLayerForwardpropagationHiddenLayerInitializationOutputLayerInputLayerStepFunctionOverfittingConvolution(CNN)ActivationFunction /ThresholdSigmoidFunctionPerceptronPerceptronGradientDescentComputerVisionWeightsNode/WeightedSumBiasesNode/WeightedSumFeedForwardFeedForwardForwardPropagationClassificationInitializationError/CostFunctionSupervised/UnsupervisedConvolution/ CNNHiddenLayerBiasesBackPropagationStepFunctionActivationFunction/ThresholdDeepLearningSupervised/UnsupervisedClassificationBackpropagationInputLayerDeepLearningBlack Box(Interpretability)BlackBoxOverfittingComputerVisionWeightsSigmoidFunctionRecurrent(RNN)Recurrent/ RNNGradientDescentError/CostFunctionOutputLayerForwardpropagationHiddenLayerInitializationOutputLayerInputLayerStepFunctionOverfittingConvolution(CNN)ActivationFunction /ThresholdSigmoidFunctionPerceptronPerceptronGradientDescent

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