Jaguares y Serpientes
Uso de Python y ArcPy para analizar datos de telemetría en la conservación de jaguares, combinando tecnología y ecología para entender y proteger esta especie.
Introducing Incompatible Changes in Python
Explore Python's evolution, focusing on introducing incompatible changes, lessons learned from Python 2 to 3 transition, and future plans for a stable ABI and improved compatibility.
Inside CPython 3.11's New Specializing, Adaptive Interpreter
Explore Python 3.11's new specializing, adaptive interpreter, its self-optimizing techniques, and performance improvements, with insights on future enhancements and optimization challenges.
The ChatGPT Privacy Tango - Dancing with Data Security and Large Language Models
Explore balancing privacy and utility in AI language models, focusing on protecting sensitive data while maximizing ChatGPT's benefits. Learn about PII removal, secure enclaves, and privacy-aware LLM applications.
Breaking Away from the Empire - Avoiding the Evil Clutches of If-Then Statements
Learn to create a hyperspace navigation app using graphs in Python, replacing complex if-then statements for improved code readability and flexibility. Explore graph data structures and modeling techniques.
Python Meets Heterogeneous Computing - An Exploration of Distributed Computations
Exploring distributed computations in Python across diverse hardware, addressing challenges and strategies for optimal performance in heterogeneous computing environments.
Breaking Boundaries - Advancements in High-Performance AI/ML through PyTorch's Python Compiler
Explore PyTorch's innovative Python compiler, designed to enhance AI/ML performance while maintaining Python roots. Learn about the development process, challenges, and significant performance improvements achieved.
Modern, Typed Python for Multimodal ML - From Training to Deployment
Explore the benefits of Python type hints in machine learning, from improving code quality to organizing multimodal data and bridging the gap between training and deployment.
Using Python to Power Serverless Applications
Explore best practices for building serverless solutions with Python, focusing on API calls, streaming data, and ML inference. Learn techniques for production-grade systems with observability.
Accelerate Your Workflow from Local Python Prototype to the Cloud
Streamline Python app deployment from local to cloud with CLI templates. Scaffold, provision, deploy, monitor, and set up CI/CD pipeline efficiently, saving time on infrastructure setup and configuration.
How to Monitor and Troubleshoot Applications Using OpenTelemetry
Explore OpenTelemetry for efficient application monitoring and troubleshooting. Learn to detect issues, track performance, and enhance observability in cloud-based environments using this open-source protocol.
Instrumentation Nightmares - A Review of Our Toughest Cases
Explore advanced Python instrumentation techniques, challenging real-world cases, and design patterns. Learn to hook into import systems, instrument popular libraries, and make your code instrumentation-friendly.
Eroding Coastlines - A Geospatial & Computer Vision Analysis
Explore satellite imagery and Python tools for geospatial analysis to identify and analyze coastal erosion, addressing a critical environmental and humanitarian challenge.
Building a Model Prediction Server
Learn to create a FastAPI application that serves real-time predictions from a trained scikit-learn model, bridging the gap between model development and production deployment.
How to Troubleshoot and Monitor Applications Using OpenTelemetry
Learn to instrument, monitor, and troubleshoot Python applications using OpenTelemetry. Gain hands-on experience with traces, metrics, and logs for improved observability and faster issue resolution.
Automate Documentation with Sphinx & GitHub Actions
Learn to create, generate, host, and automate up-to-date API documentation using Sphinx and GitHub Actions, integrating it seamlessly into your software development lifecycle.
Power Up Your Work with Compiling and Profiling
Discover how to optimize Python code performance using Numba, a JIT compiler for numerical calculations. Learn when and how to apply Numba effectively to speed up math-heavy code in data science and development projects.
The How and Why of Object-oriented Programming in Python
Comprehensive guide to object-oriented programming in Python, covering design, inheritance, special methods, and converting procedural code to OOP through practical examples.
Write Your First Package Using Literate Programming
Aprenda a criar um pacote Python usando programação literária, combinando explicações em linguagem natural com código. Explore ferramentas como Jupyter Notebooks e Nbdev para desenvolvimento eficiente e documentação integrada.
Feature Engineering is for Everyone
Explore feature engineering techniques for data visualization, automation, and machine learning. Learn to create and select features from various data types using encodings, vectorization, and date manipulation.
Data of Unusual Size - Interactive Visualization
Learn techniques for analyzing and visualizing massive datasets using Python libraries like Dask and hvPlot. Explore efficient data formats, parallel computation, cloud resources, and interactive visualization for large-scale data science projects.