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Explore Python function internals, including argument handling, variable scoping, and bytecode. Gain deeper understanding of function objects and their attributes.
Explore the fusion of art and code through generative algorithms, creating autonomous aesthetic forms using Processing and PyCairo. Learn about randomness, shapes, and advanced techniques like fractals and genetic algorithms.
Explore data regression testing with pytest-regressions to enhance test completeness for complex data structures, simplifying testing of datasets, objects, and APIs.
Interactive Python tools for image processing, combining Dash for web apps and scikit-image for advanced algorithms. Explore, annotate, and analyze scientific and business images efficiently.
Explore Python's growing role in High Energy Physics, from its adoption and key libraries to its impact on data analysis and machine learning in particle physics research.
Explore Python-based CVE Binary Tool for detecting software vulnerabilities. Learn its functionality, usage, and contribute to enhancing cybersecurity for all.
Demystifying Unicode: Learn its history, concepts, and practical implementation in Python, including handling text, encodings, and special characters.
Explora la importancia de la documentación en proyectos Python, tipos de documentación y herramientas para crearla y mantenerla eficazmente, mejorando la adopción y usabilidad del software.
Detección automatizada de malware en PyPI: vectores de ataque, sistema de detección integrado, tipos de chequeos implementados y cómo combatir amenazas en el repositorio.
Discover powerful debugging techniques beyond print statements. Learn to use command-line and graphical debuggers to examine program state, modify variables, and efficiently troubleshoot complex code situations.
Learn to deploy a Django project on serverless infrastructure using Google Cloud Platform. Covers manual deployment, database setup, media storage, secrets management, and automation techniques.
Learn advanced data visualization techniques using Python libraries to effectively communicate complex data across various fields, from choosing plots to aesthetic decisions.
Learn to build a GitHub bot that greets contributors, using Python libraries like gidgethub and asyncio. Create an app that thanks maintainers and first-time contributors, enhancing project engagement.
Comprehensive introduction to NLP in Python, covering traditional approaches, advanced concepts, and state-of-the-art language models. Includes practical applications and performance-boosting techniques.
Learn to develop machine learning models on encrypted data using CrypTen, a PyTorch-based framework for secure computing. Explore feature aggregation, data labeling, dataset augmentation, and model hiding techniques.
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