GhibliField

序号	出版社一般写法	出版地	备注
1	AAAI	Menlo Park, CA	Association for the Advancement of Artificial Intelligence
2	Academic	同Elsevier	Academic Press is part of Elsevier
3	Academy Press	New York/ London/ Paris/ San Diedo,CA/ San Francisco,CA/ Sao Paulo/ Sydney/ Tokyo/Toronto	AP，Academy Press
4	ACL	Stroudsburg,PA	Association for Computational Linguistics
5	ACM	New York, NY	ACM Press,Association for Computing and Machinery
6	AP Professional	Boston,MA/ San Diedo,CA/New York/ London/ Sydney/ Tokyo/ Toronto
7	Chapman & Hall	London/ Glasgow/ Weinheim/ New York/ Madras	CH

cbaziotis

def dot_product(x, kernel):
    """
    Wrapper for dot product operation, in order to be compatible with both
    Theano and Tensorflow
    Args:
        x (): input
        kernel (): weights
    Returns:
    """
    if K.backend() == 'tensorflow':

Mistobaan

# from https://cloud.google.com/solutions/machine-learning-with-financial-time-series-data
def tf_confusion_metrics(model, actual_classes, session, feed_dict):
  predictions = tf.argmax(model, 1)
  actuals = tf.argmax(actual_classes, 1)

  ones_like_actuals = tf.ones_like(actuals)
  zeros_like_actuals = tf.zeros_like(actuals)
  ones_like_predictions = tf.ones_like(predictions)
  zeros_like_predictions = tf.zeros_like(predictions)

japerk

Sentence Tokenization

>>> from nltk import tokenize >>> para = "Hello. My name is Jacob. Today you'll be learning NLTK." >>> sents = tokenize.sent_tokenize(para) >>> sents ['Hello.', 'My name is Jacob.', "Today you'll be learning NLTK."]