Natural Language Processing (NLP) with Google Colab Training Course
Course Outline
Introduction to Natural Language Processing (NLP)
- Overview of Natural Language Processing
- Significance of NLP in contemporary artificial intelligence applications for government
- Prominent libraries for NLP: NLTK, SpaCy, and Hugging Face
Text Preprocessing Techniques
- Tokenization and removal of stop words
- Stemming and lemmatization processes
- Methods for text normalization
Sentiment Analysis
- Overview of sentiment analysis
- Conducting sentiment analysis using NLTK
- Utilizing SpaCy for advanced sentiment analysis for government applications
Advanced NLP Techniques
- Named entity recognition (NER)
- Text classification methods
- Language modeling with pre-trained models for enhanced accuracy and efficiency
Working with Google Colab
- Introduction to the Google Colab environment for government use
- Setting up and managing NLP projects in Colab for government
- Collaborating on NLP tasks within the Colab platform
Real-World Applications of NLP
- Utilization of NLP in healthcare, finance, and customer support for government operations
- Implementing NLP for chatbots and virtual assistants to improve public services
- Emerging trends in NLP research and their implications for government
Summary and Next Steps
Requirements
- Basic understanding of natural language processing concepts for government applications
- Familiarity with Python programming
- Experience with Jupyter Notebooks or similar development environments
Audience
- Data scientists working in government agencies
- Developers with experience in Python for government projects
- AI enthusiasts interested in public sector applications
Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.
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