Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...
An exercise-driven course on Advanced Python Programming that was battle-tested several hundred times on the corporate-training circuit for more than a decade. Written by David Beazley, author of the ...
A Tutorial on how to Connect Python with Different Simulation Software to Develop Rich Simheuristics
Abstract: Simulation is an excellent tool to study real-life systems with uncertainty. Discrete-event simulation (DES) is a common simulation approach to model time-dependent and complex systems.
When Brisbane resident Rachel Bloor woke up to discover a carpet python curled up on top of her, she was rattled. The two-and-a-half-metre snake crawled onto her bed late on Monday evening. When Bloor ...
Welcome to the Python Learning Roadmap in 30 Days! This project is designed to guide you through a structured 30-day journey to learn the Python programming language from scratch and master its ...
Not everyone can declare themselves “benevolent dictator for life” of a company, but such was the nature of Guido van Rossum, the Dutch programmer who invented an entire programming language from ...
So far, running LLMs has required a large amount of computing resources, mainly GPUs. Running locally, a simple prompt with a typical LLM takes on an average Mac ...
Please note that these are just the code examples accompanying the book, which we uploaded for your convenience; be aware that these notebooks may not be useful without the formulae and descriptive ...
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