Why do we use tf.random.set_seed(1234) before setting up a neural network

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  1. What is the purpose behind using tf.random.set_seed(1234)?
  2. Also, in the optional lab of some gradient descent algo, we use;
    if i<10000: # for preventing resource exhaustion
    if i%1000==0: print(i)
    May I know what is meant by resource exhaustion?
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The reason for setting the random seed is for reproducibility. This is to ensure that the same result is obtained when the notebook is run at different times.

As for the resource exhaustion aspect, training neural networks requires 8 ina lot of computing power, that’s why a cap is set to ensure that we are within the available compute given in the Coursera environment.

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Thank you so much…

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