Introduction to NLP : How to improve accessibility with Machine Learning

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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
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8. Machine Learning is programming with data

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11. Natural Language Process (NLP)

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

    translation Others: Text Analysis Email filters Search Result Sentiment Analysis

14. Challenges in NLP

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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

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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

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35. Challenges in NLP : Textual Accessibility Language Translation

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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

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