Course Outline

Advanced NLP Techniques

Introduction to NLP

Real-World Applications of NLP

Sentiment Analysis

Summary and Next Steps

Text Preprocessing Techniques

Working with Google Colab

  • Introduction to Google Colab environment
  • Setting up and managing NLP projects in Colab
  • Collaborating on NLP tasks in Colab
  • Introduction to sentiment analysis
  • Performing sentiment analysis with NLTK
  • Using SpaCy for advanced sentiment analysis
  • NLP in healthcare, finance, and customer support
  • Using NLP for chatbots and virtual assistants
  • Future trends in NLP research
  • Named entity recognition (NER)
  • Text classification
  • Language modeling with pre-trained models
  • Tokenization and stop words removal
  • Stemming and lemmatization
  • Text normalization techniques
  • What is Natural Language Processing?
  • Importance of NLP in modern AI applications
  • Popular libraries for NLP: NLTK, SpaCy, Hugging Face

Requirements

Audience

  • Basic understanding of natural language processing concepts
  • Familiarity with Python programming
  • Experience with Jupyter Notebooks or similar environments
  • Data scientists
  • Developers with experience in Python
  • AI enthusiasts
 14 Hours

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