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Home » Technology » Big Data & Data Science » Building Domain Specific Language Models

Course Skill Level:

Foundational

Course Duration:

1 day/s

  • Course Delivery Format:

    Live, instructor-led.

  • Course Category:

    Big Data & Data Science

  • Course Code:

    BDSLM0L21E09

Who should attend & recommended skills:

Proficient Python programmers experienced with text-based machine learning and basic experience with NumPy, pandas, NLTK, and Pytorch, TensorFlow, or Keras

Who should attend & recommended skills

  • This course is geared for proficient Python programmers who have experience with text-based machine learning who want to build the foundations of any domain-specific NLP system by creating the most a robust and efficient language model.
  • This course uses Python 3.7. It is recommended that you use the Anaconda distribution of Python and conda for managing the libraries.
  • Skill-level: Foundation-level Building Domain Specific Language Models skills for Intermediate skilled team members. This is not a basic class.
  • NumPy: Basic (1-2 years’ experience)
  • pandas: Basic (1-2 years’ experience)
  • NLTK: Basic (1-2 years’ experience)
  • PyTorch, TensorFlow or Keras for creating neural networks: Basic (1-2 years’ experience)

About this course

In this course, you will be taking on the role of an NLP data scientist atStack Exchange, a network of question-and-answer websites on topics in diverse fields. Stack Exchange has over 10M registered users and is best known for its flagship websites Stack Overflow or Ask Ubuntu. You will build statistics-focused language models using gradually more complex methods. You will evaluate and apply these models to the tasks of:
– Query completion
– Larger text generation
– Sentence selection
At the end of this course, you will be able to build the foundations of any domain-specific NLP system by creating the most a robust and efficient language model.

Skills acquired & topics covered

  • Working in a hands-on learning environment, led by our Building Domain Specific Language Models expert instructor, participants will learn about and explore:
  • Starting with building n-gram language models, which will serve as a baseline for performance evaluations,
  • Moving on to a more complex modeling technique based on RNNs,
  • Using state-of-the-art language model building with the AllenNLP framework. The AllenNLP framework helps you design and evaluate deep-learning models for nearly any NLP problem.
  • Loading and preparing the dataset
  • Building and evaluating n-gram word-based language models
  • Building a word-based language model using recurrent neural networks (RNNs) and word embeddings
  • Building a character-based language model with AllenNLP

Course breakdown / modules

  • Regular Expressions
  • Tokenization
  • Submit Your Work

  • Building Your Vocabularywith a Tokenizer
  • Submit Your Work

  • Deep Learning for Text and Sequences
  • Sequential NLP and Memory
  • Submit Your Work

  • Sequential Labeling and Language Modeling
  • Submit Your Work

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