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@iolalla
iolalla / ms.go
Created December 17, 2018 17:01
Minimal go server with logging and all the headers visible.
package main
/**
* Minimal go server with logging and all the headers visible.
*
* To build it simply
* '$go build ms.go'
*
* # To lear how to use it simply:
* $ ms --help
@iolalla
iolalla / dnsLoad.go
Last active September 14, 2017 15:12
This is a go, as go from GoLang, program to automate the load of dns export files from infoblox into Google Cloud DNS.
package main
// BEFORE RUNNING:
// ---------------
// 1. If not already done, enable the Google Cloud DNS API
// and check the quota for your project at
// https://console.developers.google.com/apis/api/dns
// 2. This sample uses Application Default Credentials for authentication.
// If not already done, install the gcloud CLI from
// https://cloud.google.com/sdk/ and run
// `gcloud beta auth application-default login`.
@iolalla
iolalla / rnn-lstm.py
Last active August 18, 2017 06:33 — forked from monikkinom/rnn-lstm.py
Tensorflow RNN-LSTM implementation to count number of set bits in a binary string
#Source code with the blog post at http://monik.in/a-noobs-guide-to-implementing-rnn-lstm-using-tensorflow/
#Original gist: https://gist.github.com/AlmostDan/a5f4b57104532a68bda2c274f8bcf16f
#Tensorboard inspirational: https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/4_Utils/tensorboard_basic.py
import numpy as np
#import random
from random import shuffle
import tensorflow as tf
NUM_EXAMPLES = 10000
@iolalla
iolalla / rnn-lstm-tensorboard.py
Last active August 18, 2017 06:32
Very simple Recursive Neural Network with Memory (Long Short Term Memory LSTM) using Tensorboard to track training.
#Source code with the blog post at http://monik.in/a-noobs-guide-to-implementing-rnn-lstm-using-tensorflow/
#Original gist: https://gist.github.com/AlmostDan/a5f4b57104532a68bda2c274f8bcf16f
#Tensorboard inspirational: https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/4_Utils/tensorboard_basic.py
import numpy as np
#import random
from random import shuffle
import tensorflow as tf
NUM_EXAMPLES = 10000