(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.
import SwiftUI | |
private class IntegerTextFieldValue: ObservableObject { | |
@Published var value = "" { | |
didSet { | |
let numbersOnly = value.filter { $0.isNumber } | |
if value != numbersOnly { | |
value = numbersOnly | |
} | |
} |
""" | |
Play with saving . | |
Closest: | |
https://github.com/tensorflow/tensorflow/issues/616#issuecomment-205620223 | |
""" | |
import numpy as np | |
import tensorflow as tf | |
from tensorflow.python.platform import gfile |
7 | |
2 | |
1 | |
0 | |
4 | |
1 | |
4 | |
9 | |
5 | |
9 |
import caffe | |
caffe.set_mode_cpu() | |
import numpy as np | |
from numpy import prod, sum | |
from pprint import pprint | |
def print_net_parameters (deploy_file): | |
print "Net: " + deploy_file | |
net = caffe.Net(deploy_file, caffe.TEST) | |
print "Layer-wise parameters: " |
# | |
# mnist_cnn_bn.py date. 5/21/2016 | |
# date. 6/2/2017 check TF 1.1 compatibility | |
# | |
from __future__ import absolute_import | |
from __future__ import division | |
from __future__ import print_function | |
import os |
# Hello, and welcome to makefile basics. | |
# | |
# You will learn why `make` is so great, and why, despite its "weird" syntax, | |
# it is actually a highly expressive, efficient, and powerful way to build | |
# programs. | |
# | |
# Once you're done here, go to | |
# http://www.gnu.org/software/make/manual/make.html | |
# to learn SOOOO much more. |
(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.
A simple example of two-way communication between IPython notebook and javascript, using a D3 widget.
View this notebook on nbviewer, but be aware that it won't work without being connected to an IPython kernel!
It's better to download the notebook itself and open it with IPython notebook.
Find it here: https://github.com/bitemyapp/learnhaskell