semihyagcioglu

"""
Find what's hot in your field based on the accepted papers in your favorite conference.
Reads a file with paper titles, possibly obtained from the conference web site.
Hint: I use Chrome's developer tools to format the conference web page to simplify 
the list and paste it into a txt file. It often takes a few minutes for me.

- Semih Yagcioglu
"""

from sklearn.feature_extraction.text import CountVectorizer

semihyagcioglu

import numpy as np
from keras.models import Sequential
from keras.layers.core import Dense

X = np.array([[0,0],[0,1],[1,0],[1,1]]) # training data, the states of the XOR gate
y = np.array([[0],[1],[1],[0]]) # true labels of the data in the same order

model = Sequential()
model.add(Dense(16, input_dim=2, activation='relu'))
model.add(Dense(1, activation='sigmoid'))

semihyagcioglu

import tensorflow as tf

tf.__version__

# Creates a graph.
a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')
b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, 2], name='b')
c = tf.matmul(a, b)

# Creates a session with log_device_placement set to True.

semihyagcioglu

# !/usr/bin/env python
import sys
import numpy as np
import numpy.random as npr
from numpy.distutils.system_info import get_info
import time


if __name__ == '__main__':