Course Outline

Introduction to NLP Fine-Tuning for Government

  • What is fine-tuning?
  • Benefits of fine-tuning pre-trained language models for government
  • Overview of popular pre-trained models (GPT, BERT, T5)

Understanding NLP Tasks for Government

  • Sentiment analysis
  • Text summarization
  • Machine translation
  • Named Entity Recognition (NER)

Setting Up the Environment for Government

  • Installing and configuring Python and libraries
  • Using Hugging Face Transformers for NLP tasks in government applications
  • Loading and exploring pre-trained models for government use

Fine-Tuning Techniques for Government

  • Preparing datasets for NLP tasks in the public sector
  • Tokenization and input formatting for government data
  • Fine-tuning for classification, generation, and translation tasks specific to government operations

Optimizing Model Performance for Government

  • Understanding learning rates and batch sizes in the context of government projects
  • Using regularization techniques for enhanced model reliability in public sector applications
  • Evaluating model performance with metrics relevant to government workflows

Hands-On Labs for Government

  • Fine-tuning BERT for sentiment analysis in government documents
  • Fine-tuning T5 for text summarization of public sector reports
  • Fine-tuning GPT for machine translation of multilingual government communications

Deploying Fine-Tuned Models for Government

  • Exporting and saving models for government use
  • Integrating models into government applications
  • Basics of deploying models on cloud platforms compliant with government standards

Challenges and Best Practices for Government

  • Avoiding overfitting during fine-tuning in government projects
  • Handling imbalanced datasets in public sector data sets
  • Ensuring reproducibility in experiments for government accountability

Future Trends in NLP Fine-Tuning for Government

  • Emerging pre-trained models suitable for government use
  • Advances in transfer learning for NLP in the public sector
  • Exploring multimodal NLP applications for enhanced government services

Summary and Next Steps for Government

Requirements

  • Basic understanding of natural language processing (NLP) concepts
  • Experience with Python programming
  • Familiarity with deep learning frameworks such as TensorFlow or PyTorch

Audience

  • Data scientists for government and public sector organizations
  • NLP engineers for government and public sector projects
 21 Hours

Number of participants


Price per participant

Upcoming Courses

Related Categories