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Introduction to NLP : How to improve accessibil...

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Avatar for Victoria Ubaldo Victoria Ubaldo
June 11, 2021
Technology
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Introduction to NLP : How to improve accessibility with Machine Learning

WWCode CONNECT REIMAGINE 2021

Avatar for Victoria Ubaldo

Victoria Ubaldo

June 11, 2021
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Transcript

  1. None

  2. Victoria Ubaldo @Vikyale Introduction to NLP : How to improve

    accessibility with Machine Learning CONNECT REIMAGINE 2021

  3. Hello! Computer and System Engineer. Peruvian Data Analyst @Interbank Msc

    Candidate Computer Science, PUCP. Enjoy mentoring, illustration and dancing!

  4. Agenda • Machine Learning and Accessibility • Natural Language Processing

    • Tensorflow for NLP • Next steps
  5. None
  6. None
  7. None

  8. Machine Learning is programming with data

  9. None
  10. None

  11. Natural Language Process (NLP)

  12. None

  13. Where find NLP ? Chatbots Predictive text (autocomplete) Transcription Language

    translation Others: Text Analysis Email filters Search Result Sentiment Analysis

  14. Challenges in NLP

  15. None

  16. Challenges in NLP : Textual Accessibility Visual Auditory Speech

  17. Accessible = Comprehensible

  18. Challenges in NLP : Textual Accessibility Transcription Speech recognition Language

    Translation

  19. Case : Recognize sentiment in Text

  20. None

  21. Amazon and Yelp reviews 1 : Good 0: Bad

  22. Pre-processing data

  23. Text Processing

  24. Tokenization

  25. Out Of Vocabulary (OOV) EXTRA WORDS unknown tokens (UNK)

  26. Stop Words

  27. Stemming

  28. Lemmatization

  29. Padding

  30. Tools! • Python 3.+ • Jupyter Notebook or Google Colab

    • and using a framework for ML

  31. ¿Why Tensorflow? Whether you’re an expert or a beginner, TensorFlow

    is an end-to-end platform that makes it easy for you to build and deploy ML models.

  32. Trying in Google Colab bit.ly/2TU9MJz

  33. Challenges in NLP : Textual Accessibility Transcription Speech recognition

  34. None

  35. Challenges in NLP : Textual Accessibility Language Translation

  36. None

  37. Next steps Try new tools : - Recurrent Neural Network

    (RNN) - Long short-term memory (LSTM)

  38. Next steps Increase your corpus with diverse data. - PDFMiner

    - Tweepy API

  39. Next steps Datasets with native or indigenous language or code

    mixing

  40. “We can build a much brighter future where humans are

    relieved of menial work using AI capabilities” - Andrew Ng

  41. Thanks! @womenwhocode #WWCode Keep in touch! linkedin.com/in/victoriaubaldo @vikyale

  42. None