jbochi

impredicative

"""
Usage example:

    from logger import get_logger
    log = get_logger()
    log.info('my_event', my_key1='val 1', my_key2=5, my_key3=[1, 2, 3], my_key4={'a': 1, 'b': 2})

List of metadata keys in each log message:
    event
    _func

udibr

import numpy as np
from keras.layers import GRU, initializations, K
from collections import OrderedDict

class GRULN(GRU):
    '''Gated Recurrent Unit with Layer Normalization
    Current impelemtation only works with consume_less = 'gpu' which is already
    set.

    # Arguments

aabadie

"""Example of usage of Joblib with Amazon S3."""

import s3io
import joblib
import numpy as np

big_obj = [np.ones((500, 500)), np.random.random((1000, 1000))]

# Customize the following values with yours
bucket = "my-bucket"

atduskgreg

Interactive Machine Learning

Taught by Brad Knox at the MIT Media Lab in 2014. Course website. Lecture and visiting speaker notes.

• Power to the People: The Role of Humans in Interactive Machine Learning by Knox, Cakmak, Kulesza, Amershi, and Lau
• A Few Useful Things to Know about Machine Learning by Domingos
• Machine Learning that Matters by Wagstaff
• Beyond Concise and Colorful: Learning Intelligible Rules by Pazzani et al.
• [Designing Games with a Purpose] (https://www.cs.cmu.edu/~biglou/GWAP_CACM.pdf) by von Ahn and Dabbish
• [Human Model Evaluation in Interactive Supervised

tomrunia

import numpy as np
from tensorflow.python.summary.event_accumulator import EventAccumulator

import matplotlib as mpl
import matplotlib.pyplot as plt

def plot_tensorflow_log(path):

    # Loading too much data is slow...
    tf_size_guidance = {

felipou

#!/bin/bash
#
# Created by Felipe Machado - 2016/02/14
#
# A retry command for bash
# Retries the given command up to MAX_RETRIES, with an interval of SLEEP_TIME
# between each retry. Just put it on your bash_profile and be happy :)
# Usage:
#   retry [-s SLEEP_TIME] [-m MAX_RETRIES] COMMAND_WITH_ARGUMENTS
#

mmmikael

from __future__ import absolute_import
from __future__ import print_function
import numpy as np
np.random.seed(1337)  # for reproducibility

import random
from keras.datasets import mnist
from keras.models import Sequential
from keras.layers.core import *
from keras.optimizers import SGD, RMSprop

matburt

(defun org-idonethis-capture ()
  "Captures captures and sends them to idonethis"
  (message "before hook")
  (cond ((string-match "\:tag-to-match\:" (buffer-string))
         (goto-char (point-min))
         (search-forward "****")
         (setq note-contents (buffer-substring (+ (point) 1) (line-end-position)))
         (message note-contents)
         (request
          "https://idonethis.com/api/v0.1/dones/"

bmabey