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You're reading from  Natural Language Processing with Python Quick Start Guide

Product typeBook
Published inNov 2018
Reading LevelIntermediate
PublisherPackt
ISBN-139781789130386
Edition1st Edition
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Nirant Kasliwal
Nirant Kasliwal
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Nirant Kasliwal

Nirant Kasliwal maintains an awesome list of NLP natural language processing resources. GitHub's machine learning collection features this as the go-to guide. Nobel Laureate Dr. Paul Romer found his programming notes on Jupyter Notebooks helpful. Nirant won the first ever NLP Google Kaggle Kernel Award. At Soroco, image segmentation and intent categorization are the challenges he works with. His state-of-the-art language modeling results are available as Hindi2vec.
Read more about Nirant Kasliwal

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Why chatbots as a learning example?

So far, we have built an application for every NLP topic that we have seen:

  • Text cleaning using grammar and vocabulary insights
  • Linguistics (and statistical parsers), to mine questions from text
  • Entity recognition for information extraction
  • Supervised text classification using both machine learning and deep learning
  • Text similarity using text-based vectors such as GloVe/word2vec

We will now combine all of them into a much more complicated setup and write our own chatbot from scratch. But, before you build anything from scratch, you should ask why.

Why build a chatbot?

A related questions is why should we build our own chatbots? Why can't I use FB/MSFT/some other cloud service?

Perhaps...

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Natural Language Processing with Python Quick Start Guide
Published in: Nov 2018Publisher: PacktISBN-13: 9781789130386

Author (1)

author image
Nirant Kasliwal

Nirant Kasliwal maintains an awesome list of NLP natural language processing resources. GitHub's machine learning collection features this as the go-to guide. Nobel Laureate Dr. Paul Romer found his programming notes on Jupyter Notebooks helpful. Nirant won the first ever NLP Google Kaggle Kernel Award. At Soroco, image segmentation and intent categorization are the challenges he works with. His state-of-the-art language modeling results are available as Hindi2vec.
Read more about Nirant Kasliwal