Natural Language Processing: Getting Started with NLP

Natural Language Processing    |    Intermediate
  • 12 Videos | 40m 26s
  • Includes Assessment
  • Earns a Badge
Enterprises across the world are creating large amounts of language data. There are many different kinds of data with language components including reports, word documents, operational data, emails, reviews, sops, and legal documents. This course will help you develop the skills to analyze this data and extract valuable and actionable insights. Learn about the various building blocks of natural language processing to help in understanding the different approaches used for solving NLP problems. Examine machine learning and deep learning approaches to handling NLP issues. Finally, explore common use cases that companies are approaching with NLP solutions. Upon completion of this course, you will have a strong foundation in the fundamentals of natural language processing, its building blocks, and the various approaches that can be used to architect solutions for enterprises in NLP domains.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    describe the foundation of natural language and its processing
    illustrate phonemes, morpheme, and lexemes
    describe syntactic and semantic analysis for NLP
    illustrate various fundamental tasks and components that are solved and explored using NLP
    describe heuristic approaches to solve NLP tasks
  • describe machine learning approaches to solve NLP tasks
    describe deep learning approaches to solve NLP tasks
    specify challenges with NLP in real world problem solving
    illustrate various tools in NLP used across different industries
    illustrate various use cases in NLP across different industries
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    55s
    UP NEXT
  • Playable
    2. 
    What is Natural Language Processing (NLP)
    4m 33s
  • Locked
    3. 
    Building Blocks of Language
    2m 43s
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    4. 
    Syntactic and Semantic Analysis
    2m 57s
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    5. 
    Various Tasks of NLP
    2m 21s
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    6. 
    Heuristics-based NLP
    4m 36s
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    7. 
    Machine Learning-based NLP
    5m 32s
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    8. 
    Deep Learning-based NLP
    5m 4s
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    9. 
    Challenges with NLP
    4m 11s
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    10. 
    Tool Ecosystem of NLP
    4m 45s
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    11. 
    NLP Use Cases in Industry
    2m 16s
  • Locked
    12. 
    Course Summary
    34s

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