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TensorFlow Deep Learning Projects

You're reading from   TensorFlow Deep Learning Projects 10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning

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Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781788398060
Length 320 pages
Edition 1st Edition
Languages
Concepts
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Authors (5):
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Alberto Boschetti Alberto Boschetti
Author Profile Icon Alberto Boschetti
Alberto Boschetti
Rajalingappaa Shanmugamani Rajalingappaa Shanmugamani
Author Profile Icon Rajalingappaa Shanmugamani
Rajalingappaa Shanmugamani
Luca Massaron Luca Massaron
Author Profile Icon Luca Massaron
Luca Massaron
Abhishek Thakur Abhishek Thakur
Author Profile Icon Abhishek Thakur
Abhishek Thakur
Alexey Grigorev Alexey Grigorev
Author Profile Icon Alexey Grigorev
Alexey Grigorev
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Toc

Table of Contents (12) Chapters Close

Preface 1. Recognizing traffic signs using Convnets 2. Annotating Images with Object Detection API FREE CHAPTER 3. Caption Generation for Images 4. Building GANs for Conditional Image Creation 5. Stock Price Prediction with LSTM 6. Create and Train Machine Translation Systems 7. Train and Set up a Chatbot, Able to Discuss Like a Human 8. Detecting Duplicate Quora Questions 9. Building a TensorFlow Recommender System 10. Video Games by Reinforcement Learning 11. Other Books You May Enjoy

Preprocessing of the corpora

The first step is to retrieve the corpora. We've already seen how to do this, but let's now formalize it in a function. To make it generic enough, let's enclose these functions in a file named corpora_tools.py.

  1. Let's do some imports that we will use later on:
import pickle
import re
from collections import Counter
from nltk.corpus import comtrans
  1. Now, let's create the function to retrieve the corpora:
def retrieve_corpora(translated_sentences_l1_l2='alignment-de-en.txt'):
print("Retrieving corpora: {}".format(translated_sentences_l1_l2))
als = comtrans.aligned_sents(translated_sentences_l1_l2)
sentences_l1 = [sent.words for sent in als]
sentences_l2 = [sent.mots for sent in als]
return sentences_l1, sentences_l2

This function has one argument; the file containing the aligned sentences from...

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