SKILL BENCHMARK

Deep Learning for Natural Language Processing Literacy (Beginner Level)

  • 10m
  • 10 questions
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The Deep Learning for Natural Language Processing Literacy (Beginner Level) benchmark measures your basic understanding of deep learning techniques and concepts for developing natural language processing (NLP) applications. Learners who score high on this benchmark demonstrate that they have a good understanding of deep learning frameworks and techniques used for NLP application development.

Topics covered

  • define basic concepts of sentiment data
  • describe RNN Architecture and how it can capture context in language
  • explore the end-to-end components for a natural language processing (NLP) sentiment dataset
  • illustrate MLP Architecture of Neural Network
  • illustrate single layer perceptron architecture of a neural network
  • illustrate various use cases in NLP across different industries
  • outline the basic concepts of Keras and PyTorch
  • outline the basic concepts of Open Neural Machine Translation (OpenNMT) and DeepNL
  • outline the basic concepts of spaCy and TensorFlow
  • recall basic concepts of natural language processing (NLP) with deep learning (DL)