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
• Self-Paced
• Free Video

Exploring Big Data with cuDF Pandas - A Step-by-Step Guide Using GPU Acceleration

Dive into big data analysis with cuDF Pandas, a GPU-accelerated framework, using the American Stories dataset. Learn to download, visualize, and analyze large datasets with syntax similar to pandas but with the speed advantages of GPU processing.

• YouTube
• 17 minutes
• Self-Paced
• Free Video

Mastering Data Manipulation with CUDA Accelerated Pandas with cuDF - Hands-on Guide

Master data manipulation techniques using CUDA-accelerated Pandas (cuDF) to achieve significant speed improvements with GPU acceleration while maintaining compatibility with existing pandas code.

• YouTube
• 10 minutes
• Self-Paced
• 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
• Self-Paced
• Free Video

Accelerating Pandas with NVIDIA's cuDF: Basic Statistical Analysis and Data Cleaning - Episode 6

Discover how to accelerate statistical analysis and data cleaning on large datasets using NVIDIA's cuDF, a GPU-powered alternative to Pandas, with performance comparisons between CPU and GPU processing.

• YouTube
• 15 minutes
• Self-Paced
• Free Video

Speed up Cleaning Data with Pandas and your GPU - CuDF Episode 5

Master GPU-accelerated data cleaning with cuDF, NVIDIA's CUDA version of Pandas. Learn to handle missing values, drop columns, and convert data types for efficient processing of large datasets.

• YouTube
• 12 minutes
• Self-Paced
• Free Video

Time Series Analysis on a GPU with Pandas and cuDF - Episode 7

Discover how to accelerate time series analysis using cuDF, a GPU-powered Pandas alternative, to efficiently process and visualize historical newspaper data with practical demonstrations on a high-performance workstation.

• YouTube
• 11 minutes
• Self-Paced
• 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
• Self-Paced
• Free Video

SpaCy for Digital Humanities with Python

Master spaCy for natural language processing in digital humanities projects through comprehensive Python tutorials covering NER, text analysis, and model training.

• YouTube
• 11 hours 3 minutes
• Self-Paced
• Free Video

Topic Modeling and Text Classification with Python for Digital Humanities

Discover topic modeling and text classification techniques using Python libraries like Scikit-Learn, Gensim, and spaCy for digital humanities research and analysis.

• YouTube
• 3 hours 58 minutes
• Self-Paced
• Free Video

An Introduction to Python for the Digital Humanities

Discover Python programming fundamentals tailored for humanities scholars with no coding experience, covering data handling, web scraping, and text analysis techniques.

• YouTube
• 9 hours 49 minutes
• Self-Paced
• Free Video

Pandas Python Tutorials - Complete Beginner's Guide to Data Analysis

Master Pandas from scratch with comprehensive tutorials covering DataFrames, data cleaning, filtering, grouping, and visualization for Python beginners.

• YouTube
• 2 hours 1 minute
• Self-Paced
• Free Video

Named Entity Recognition in Python for Digital Humanities

Master named entity recognition techniques using Python, spaCy, and Gensim to extract structured data from unstructured texts for digital humanities research projects.

• YouTube
• 6 hours 26 minutes
• Self-Paced
• Free Video

Latin Natural Language Processing with Python and CLTK

Explore Latin text analysis using Python and CLTK tools, covering tokenization, lemmatization, and custom named entity recognition for classical texts.

• YouTube
• 2 hours 49 minutes
• Self-Paced
• Free Video

Machine Learning for Digital Humanities

Discover machine learning and neural networks designed specifically for humanities scholars without mathematical backgrounds using TensorFlow and Keras.

• YouTube
• 2 hours 58 minutes
• Self-Paced
• Free Video