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#%% (0) Important libraries | |
import tensorflow as tf | |
import numpy as np | |
from numpy import random | |
import matplotlib.pyplot as plt | |
from IPython import display | |
% matplotlib inline | |
#%% (1) Dataset creation. |
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# Code for https://www.data-blogger.com/2017/12/14/create-a-character-based-seq2seq-using-python-and-tensorflow/ | |
# Imports | |
import tensorflow as tf | |
import pandas as pd | |
from nltk import word_tokenize | |
from collections import Counter | |
import numpy as np | |
# Load the data |
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# The goal of this Gist is to implement a simple (Logistic Regression) model such that most of the functionalities of Chainer are used | |
# @author K.M.J. Jacobs | |
# @date 2018-02-24 | |
# @website https://www.data-blogger.com | |
import chainer | |
from chainer import reporter as reporter_module | |
from chainer.training.extensions import LogReport | |
from chainer import iterators | |
from chainer import training |