Leveraging Deep Learning for Natural Language Processing

Nivå: Intermediate

Starting with the basics, this course teaches you how to choose from the various text pre- processing techniques and select the best model from the several neural network architectures for NLP issues.

Nyckelfunktioner:

  • After-course instructor coaching benefit
  • After-course computing sandbox included
  • Learning Tree end-of-course exam included

Du kommer lära dig att:

  • Understand various pre-processing techniques for deep learning problems
  • Build a vector representation of text using word2vec and GloVe
  • Create a named entity recognizer and parts-of-speech tagger with Apache OpenNLP
  • Build a machine translation model in Keras
  • Develop a text generation application using LSTM
  • Build a trigger word detection application using an attention model

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LIVE, LÄRARLEDD

I klass & Live, Online-utbildning

  • 3-day instructor led training course
  • One-on-one after-course instructor coaching
  • Pay later by invoice -OR- at the time of checkout by credit card

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  • Fullskalig programutveckling
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  • Coaching av ett expertteam

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Learning Tree erbjuder kundanpassad utbildning hos er, öppna kurser i Stockholm, London eller Washington, möjlighet att delta via våra Anywhere centers (Malmö, Göteborg, Linköping, Stockholm eller Borlänge) eller olika former av e-learning med lärarstöd. Läs mer på www.learningtree.se/priser .

I klass & Live, Online-utbildning

Note: This course runs for 3 dagar

  • 30 nov - 2 dec 9:00 - 16:30 GMT Online (AnyWare) Online (AnyWare) Boka Din Kursplats

  • 22 - 24 feb 9:00 - 16:30 GMT Online (AnyWare) Online (AnyWare) Boka Din Kursplats

  • 3 - 5 maj 9:00 - 16:30 BST Online (AnyWare) Online (AnyWare) Boka Din Kursplats

  • 19 - 21 jul 9:00 - 16:30 BST Online (AnyWare) Online (AnyWare) Boka Din Kursplats

  • 27 - 29 sep 9:00 - 16:30 BST Online (AnyWare) Online (AnyWare) Boka Din Kursplats

  • 22 - 24 nov 15:00 - 22:30 CCET Ottawa / Online (AnyWare) Ottawa / Online (AnyWare) Boka Din Kursplats

  • 23 - 25 mar 14:00 - 21:30 CCET New York / Online (AnyWare) New York / Online (AnyWare) Boka Din Kursplats

  • 25 - 27 maj 15:00 - 22:30 CCST Ottawa / Online (AnyWare) Ottawa / Online (AnyWare) Boka Din Kursplats

  • 7 - 9 sep 15:00 - 22:30 CCST New York / Online (AnyWare) New York / Online (AnyWare) Boka Din Kursplats

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När du ser symbolen för “Guaranteed to Run” vid ett kurstillfälle vet du att kursen blir av. Garanterat.

Leveraging Deep Learning for Natural Language Processing Training Information

  • Requirements

    Strong working knowledge of Python, linear algebra, and machine learning is a must.

  • Who Should Attend This Course

    If you’re an aspiring data scientist looking for an introduction to deep learning in the NLP domain, this is just the book for you.

Leveraging Deep Learning for Natural Language Processing Training Outline

  • Lesson 1: Introduction to Natural Language Processing

    • Basics of Natural Language Processing & application areas.
    • Introduction to popular text pre-processing techniques.
    • Introduction to word2vec and Glove word embeddings.
    • Sentiment classification.
  • Lesson 2: Applications of Natural Language Processing

    • Introduction to Named Entity Recognition.
    • Introduction to Parts of Speech Tagging.
    • Using popular libraries to develop a Named Entity Recognizer.
  • Lesson 3: Introduction to Neural Networks

    • Introduction to Neural Networks.
    • Basics of Gradient descent and backpropagation.
    • What is Deep Learning.
    • Introduction to Keras.
    • Fundamentals of deploying a model as a service.
  • Lesson 4: Foundations of Convolutional Neural Networks

    • Introduction to CNN.
    • Understanding the architecture of a CNN.
    • Application areas of a CNN.
    • Implementation using Keras.
  • Lesson 5: Recurrent Neural Networks

    • Introduction to RNN.
    • Understanding the architecture of a RNN.
    • Application areas of a RNN.
    • Implementation using Keras.
    • Vanishing Gradients with RNN.
  • Lesson 6: Gated Recurrent Units

    • Introduction to GRU.
    • Understanding the architecture of a GRU.
    • Application areas.
    • Implementation using Keras.
  • Lesson 7: Long Short Term Memory

    • Introduction to LSTM.
    • Understanding the architecture of an LSTM.
    • Application areas.
    • Implementation using Keras.
  • Lesson 8: State of the art in Natural Language Processing

    • Attention Model & Beam search.
    • End to End models for speech processing.
    • Dynamic Neural Networks for question answering.
  • Lesson 9: A practical NLP project workflow in an organisation

    • Data acquisition (Free datasets, crowd-sourcing).
    • Using cloud infrastructure to train deep learning NLP model (Google colab notebook).
    • Writing a Flask framework server RestAPI to deploy a model.
    • Deploy the web service on cloud infrastructure (AWS ec2 instance, docker).
    • Current promising techniques in NLP (BERT and others).

Teamträning

Leveraging Deep Learning for Natural Language Processing FAQs

  • Can I take this data science course online?

    Yes! We know your busy work schedule may prevent you from getting to one of our classrooms which is why we offer convenient online training to meet your needs wherever you want, including online training.

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Why do we require your location?

It allows us to direct your request to the appropriate Customer Care team.

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