U of A DataLab Spring 2025
When
Join us in this workshop series for an engaging and accessible introduction to Natural Language Processing (NLP) and its practical applications for everyday tasks! In "NLP for All," we will explore the fundamental concepts behind NLP: From understanding how computers interpret human language; to discovering how to improve search queries, use regular expressions, find datasets, and learn about pipelines for working with language. Whether you're curious about chatbots, voice assistants, or automated text transcription and analysis, this series will demystify popular technologies and show you how they work.
What We Will Cover:
- Foundations of NLP: Gain a solid grasp of NLP concepts and terminology without needing a technical background.
- Real-World Applications: Explore practical uses of NLP in various contexts, such as improving search and information retrieval, generating and evaluating automatic transcriptions, and working with popular libraries such as spaCy, PyTorch and scikit-learn.
- Hands-On Experience: We will illustrate NLP concepts in action with a well-documented code notebook, aimed at solving practical examples. We will also explore online sources for NLP tools and datasets, such as HuggingFace.
Prerequisites:
- A Google account to run Google Colab (where we will do most of our programming exercises)
- Basic knowledge of Python. You can brush up python fundamentals with Software Carpentry's Introduction to Python (section 1)
SERIES: Natural Language Processing for All
When: Thursdays, 12:00 - 1:00 PM January 30 - April 03, 2025
Where: Register for Zoom link Albert B. Weaver Science-Engineering Library, room 212 and Zoom
Instructors: Megh Krishnaswamy
YouTube: UArizona DataLab and session links
Workshop sessions:
- 1/30 Introduction to NLP with SpaCy
- 2/6 Regular Expressions for NLP
- 2/13 Text pre-processing for NLP
- 2/20 Introduction to Information Extraction
- 2/27 NLP with Transformers
- 3/6 Introduction to Semantic Search
- 3/20 Introduction to Speech Technology
- 3/27 Speech-to-Text with Whisper AI
- 4/3 AI applications for Audio data