Python Tutorials for Digital Humanities Courses

Named Tuples in Python - Data Structures for Digital Humanities

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Discover how Named Tuples in Python enhance data organization by combining tuple efficiency with dictionary-like attribute access for clearer, more maintainable code structures.

• YouTube
• 13 minutes
• On-Demand
• Free Video

Building Network Analysis Applications with Streamlit and st-link-analysis - Python Tutorial

Learn to create interactive network analysis applications using Streamlit and st-link-analysis, featuring customizable visualizations, real-time interaction, and efficient data handling capabilities.

• YouTube
• 14 minutes
• On-Demand
• Free Video

Synthetic Data Generation and Applications in Python

Discover how to generate synthetic data for machine learning and data analysis projects, with practical Python examples and implementation strategies.

• YouTube
• 18 minutes
• On-Demand
• Free Video

Transcribing Audio and Video Using Python and Whisper-MLX ASR

Learn to implement audio and video transcription using Python and Whisper-MLX ASR, featuring step-by-step guidance on installation, setup, and execution of the transcription process.

• YouTube
• 12 minutes
• On-Demand
• Free Video

Creating and Publishing Python Packages to PyPI with Twine - 5 Easy Steps

Master the process of creating and publishing Python packages to PyPI through a step-by-step guide covering setup files, documentation, packaging with setuptools, and uploading with Twine.

• YouTube
• 13 minutes
• On-Demand
• Free Video

How to Prepare Annotations in Prodigy for Training SpaCy SpanCat Models - Part 2

Master the process of preparing and using Prodigy annotations to train SpanCat models in spaCy, focusing on data preparation, annotation techniques, and model training workflows.

• YouTube
• 12 minutes
• On-Demand
• Free Video

SpanCat with spaCy on Real Data - Cultivating Data for Annotation - Part 1

Learn how to implement SpanCat in spaCy for real-world data annotation, focusing on project setup and effective data cultivation techniques for natural language processing.

• YouTube
• 12 minutes
• On-Demand
• Free Video

Named Entity Recognition Tools in spaCy - A Comparison Guide

Master the differences between spaCy's entity recognition tools and learn when to effectively implement NER, EntityRuler, SpanCat, and SpanRuler for optimal text processing results.

• YouTube
• 11 minutes
• On-Demand
• Free Video

Coreference Resolution with spaCy and spaCy-Experimental

Master coreference resolution in Python using spaCy-Experimental - implement advanced natural language processing techniques to track and link entity mentions across text.

• YouTube
• 12 minutes
• On-Demand
• Free Video

Topic Modeling with LeetTopic - Transformer Topic Modeling and Bokeh App Generation

Learn to implement transformer-based topic modeling using LeetTopic and create interactive Bokeh visualizations for text analysis in Python.

• YouTube
• 17 minutes
• On-Demand
• Free Video

Create DataFrame Applications with Streamlit and Pandas in Python

Learn to create interactive DataFrame applications using Streamlit and Pandas with just two lines of Python code, enabling quick data visualization and manipulation.

• YouTube
• 13 minutes
• On-Demand
• Free Video

Serializing spaCy Doc Containers with DocBin and Pickle

Learn how to efficiently save and serialize spaCy Doc containers using DocBin and Pickle methods for optimized data storage and retrieval in Python.

• YouTube
• 13 minutes
• On-Demand
• Free Video

Creating Image Grids in Streamlit Using Columns - Easy Tutorial

Master Streamlit's image grid functionality using columns to display collections of images efficiently in just 30 lines of Python code.

• YouTube
• 17 minutes
• On-Demand
• Free Video

Best Way to OCR a PDF in Python with spaCy Layout

Master PDF OCR techniques using spaCy Layout in Python to extract text, detect tables, and obtain metadata with precise bounding box coordinates for document analysis.

• YouTube
• 15 minutes
• On-Demand
• Free Video

Accelerate Data Analysis with RAPIDS cuDF - Using Pandas on GPU - Episode 2

Master GPU-accelerated data analysis with cuDF, achieving 500x faster performance than traditional Pandas. Learn installation, setup, and real-world speed comparisons between CPU and GPU processing.

• YouTube
• 13 minutes
• On-Demand
• Free Video