llsourcell / how_to_use_tensorflow_for_classification-live Goto Github PK
View Code? Open in Web Editor NEWThis is the code for the "How to Use Tensorflow for Classification" live session by Siraj Raval on Youtube
how_to_use_tensorflow_for_classification-live's Issues
Weights and biases.
Why are we creating the matrix 'weight' of 2 dimensions i.e 2*2 when there are only 2 features, like we did for the biases?
Zero weights?
From here:
https://github.com/llSourcell/How_to_use_Tensorflow_for_classification-LIVE/blob/master/demo.ipynb
This code:
W = tf.Variable(tf.zeros([2, 2])) # Maintain a 2 x 2 float matrix for the weights that we'll keep updating
Won't GradientDescentOptimizer train all the weights the same if all they are initialized all the same?
Should n_samples be 10 or 20?
The code says "n_samples = inputY.size" which means n_samples is 20. Because inputY is 10 * 2 matrix.
Do we expect samples to be 20? Or should it be 10 because we only use 10 lines of training data?
Add parenthesis on print statements so that code works in python3 too!
print('yo')
print(dataframe)
print(dataframe)
print(inputX)
print(inputY)
print("Training step:", '%04d' % (i), "cost=", "{:.9f}".format(cc)) #, \"W=", sess.run(W), "b=", sess.run(b)
print("Optimization Finished!")
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