artificial-intelligence

来源： https://stackoverflow.com/questions/60003006/could-validation-data-be-a-generator-in-tensorflow-keras-2-0

来源： https://stackoverflow.com/questions/56115874/how-to-convert-bounding-box-x1-y1-x2-y2-to-yolo-style-x-y-w-h

来源： https://stackoverflow.com/questions/56115874/how-to-convert-bounding-box-x1-y1-x2-y2-to-yolo-style-x-y-w-h

来源： https://stackoverflow.com/questions/12405473/does-a-neural-network-with-sigmoid-activation-use-thresholds

来源： https://stackoverflow.com/questions/55619176/how-to-cluster-similar-sentences-using-bert

来源： https://stackoverflow.com/questions/55619176/how-to-cluster-similar-sentences-using-bert

来源： https://stackoverflow.com/questions/10626134/derivative-of-sigmoid

来源： https://stackoverflow.com/questions/52852843/using-stockfish-chess-ai-in-unity

来源： https://stackoverflow.com/questions/63072770/pytoch-runtimeerror-dimension-out-of-range-expected-to-be-in-range-of-1-0

问题 Maybe my question will seem stupid. I'm studying the Q-learning algorithm. In order to better understand it, I'm trying to remake the Tenzorflow code of this FrozenLake example into the Keras code. My code: import gym import numpy as np import random from keras.layers import Dense from keras.models import Sequential from keras import backend as K import matplotlib.pyplot as plt %matplotlib inline env = gym.make('FrozenLake-v0') model = Sequential() model.add(Dense(16, activation='relu',