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Greening the Economy: Sustainable Cities
Introduction to Graphic Illustration
Computational Social Science Methods
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Strategies and experiences for migrating large Python 2 codebases to Python 3, using a real-world case study of a CMS with nearly one million lines of code. Practical insights for successful migration projects.
Ray: open-source framework for scaling Python applications from laptop to cluster, solving performance challenges in ML/AI systems. Learn its features, use cases, and how it compares to alternatives.
Learn to optimize deep learning computations by writing custom C and CUDA extensions for GPU, with a focus on image search across billions of items and seamless integration with Python codebases.
Explore Neural Style Transfer using GANs, including challenges, technicalities, and applications in gaming, fashion, and mobile apps. Learn about loss functions and see code examples.
Discover the essentials of machine learning, neural networks, and reinforcement learning in this engaging talk. Gain practical insights and witness a mind-blowing demo to kickstart your ML journey.
Discover IPython's power for rapid development, including magic commands, external processes, and integration with existing tools. Learn popular extensions and configuration hacks applicable to Jupyter.
Explore async programming in Python, focusing on its benefits for web applications. Learn to transform Flask apps to Sanic, with tips on measuring, monitoring, and testing async code.
Explore the process of reviving and updating a Django project from Python 2.7 to 3.8, focusing on challenges, solutions, and best practices for modernizing legacy code.
Live-coding session using NumPy and SoundDevice to create realistic instrument sounds with math. Gradually build a synthesizer from simple sine waves to playing classical music, while exploring music theory concepts.
Explore Python's object internals, memory management, and data structure behavior. Gain insights into mutability, copying, sorting, and memory allocation for improved code understanding and optimization.
Explore deceptive security techniques using Python, including WebTrap and DemonHunter tools. Learn how to implement machine learning for XPath injection attack mitigation in web services.
Explore discrete event simulation for logistics using salabim, an open-source Python package. Learn to model complex systems with advanced animation and statistical features.
Practical insights on building scalable data streaming ML pipelines for real-time processing using Python, Kafka, SpaCy, and Seldon. Covers key concepts and best practices through a Reddit comment moderation case study.
Explore generative models and probabilistic programming for decision-making under uncertainty, integrating with robust optimization techniques to enhance business strategies.
Explore discrete-event simulation for robotics, boosting performance and determinism. Learn to overcome challenges in event-driven systems and distributed simulations for faster development and testing cycles.
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