Sequential modelling in NLP

Natural language processing (NLP) is the ability of a computer program to understand human language as it is spoken. NLP is a component of artificial intelligence

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About the course

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After understanding Statistical NLP,it is time to understand how to work with Recurrent neural networks & LSTMs to process and derive inference out of the text data.

Data modeling is an essential part of the data science pipeline. This, combined with the fact that it is an advantageous process, makes it the one that often receives the most attention among data science learners. However, things are not as simple as they may seem, since there is much more to it than applying a function from a particular class of a package and applying it on the data available.

In this course, you will learn about sequential data and understand the mechanisms of RNNs & LSTMs so that you can start working on the text data.

Skills you will gain

  • RNNs
  • Time series analysis
  • LSTMs
  • GRU

Course Syllabus

Module 1

Sequential modelling in NLP

2.5 Hrs

1 Quiz
  • Introduction to RNN
  • Introduction to LSTM
  • LSTM Forward Pass
  • LSTM Backprop through time
  • Hands-on demo in Keras: POS tagger using LSTM
  • LSTM Applications: Sentiment Analysis, Sentence generation, Machine Translation
  • Advanced LSTM Structures
  • Hands-on Demo in Keras: Machine Translation
  • Hands-on demo in Keras: Sentiment Analysis
  • Show more


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Course certificate

Get Sequential modelling in NLP course completion certificate from Great learning which you can share in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents.