I start keeping my references here…

batch norm

How do you know which parameters to choose for Keras (TensorFlow)?

This Example kernel, shown below, has some interesting properties.


#getting the 2D output:
output = model.get_layer("dense_3").output
extr = Model(model.input, output)



The following article is worth a look





Here’s another resource




Don’t ignore the power of Excel


Good Read…

http://www.scipy-lectures.org/

This is a good intro to python, for scientific computing:

cs231n.github.io/python-numpy-tutorial/

TODO

Look up Resnet

Python Examples for this book

RESOURCES

Deeplearning.net

This one seemed to have some cool code examples..

Numpy Stuff


# Options...left over plus any 1 
x[0]+leftOver
# will it increase the score?

# Come back to this
score = Score(x)

def lowest():
sum=100
tic=''
h=score[1]
for k in h.keys():
if h[k][0] < sum:
sum = h[k][0]
tic=k
ticN=np.fromstring(tic[1:-1], dtype=int, sep=' ')
return (tic,sum,ticN)

leftOver=total - np.sum(x,axis=0)


# What you have to work with
leftOver+lowest()[2]

def buildArrayFromScore():
a=np.array([])
for k in score[1].keys():
if a.size==0:
a=np.fromstring(k[1:-1], dtype=int, sep=' ')
else:
a=np.vstack((a,np.fromstring(k[1:-1], dtype=int, sep=' '))  ) 
return a


def ifFoundReplace(x,b,c):
if b == c:
return x
idx=np.where(np.all(x==b,axis=1))
if idx[0].size != 0:
x[idx]=np.array(c)
return x

score[1].keys()