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Explore the mathematical foundations of machine learning, from linear algebra to optimization, with practical Python implementations using NumPy, SciPy, and TensorFlow.
Maximize Python productivity with Visual Studio Code: from basic setup to advanced features like debugging, testing, and collaborative coding. Learn tips and tricks for efficient development.
Orientación para participar en sprints de desarrollo colaborativo en Python, explorando oportunidades de contribución y mejora de proyectos de código abierto.
Explore techniques to optimize Python startup speed by embedding code objects into the cPython binary, reducing module loading time and improving performance for frequently launched applications.
Explore CPython's inner workings: from code compilation to execution. Learn about tokenization, parsing, bytecode, and the stack-based virtual machine, suitable for Python developers of all levels.
Explore tree-based ensemble models like Random Forest and Gradient Boosting, understanding their theory and implementation in Python for effective data science applications.
Explore data-driven humanitarian and healthcare projects using Python, with audience experiments and inspiration for running your own scientific experiments using the Python stack.
Explore Python-based online tools for analyzing air quality data, integrating libraries like Pandas and NumPy with Django and Plot.ly to create interactive visualizations and support research and education.
Explore Quart, an asyncio-based alternative to Flask, offering enhanced features like HTTP/2 and websockets while maintaining Flask's API for efficient web development.
Explore Pickle's security risks, potential defenses, and alternatives for safe Python object serialization in distributed systems.
Explore how AWS Lambda and Python concurrency can optimize a genetic algorithm for winning the SushiGo card game, discussing implementation, challenges, and results.
Explore strategies to manage software complexity, prevent common pitfalls, and foster a culture of craftsmanship for sustainable development and improved project outcomes.
Learn to craft clear, actionable error messages for better code readability and user experience. Explore common pitfalls and effective techniques for writing informative error messages in Python.
Learn to analyze, manipulate, and visualize geospatial data using Python and open-source modules like Shapely, Fiona, rasterio, and GeoPandas. Explore vector and raster data handling, spatial reference systems, and map creation.
Explore debugging techniques using data visualization tools to understand complex code behavior, illustrated with real-world examples from AWS CLI and boto3 development.
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