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SigOpt stories

SigOpt is a tool centered around optimizing complex models and processes. At its core, it leverages techniques like Bayesian optimisation to enhance the performance of various modelling tasks.

Exploring stories tagged with SigOpt offers insights into how advanced optimisation methods can identify optimal parameters efficiently, especially when dealing with black-box functions or unknown landscapes. Reading these articles can help deepen your understanding of modern optimisation strategies and their practical applications in data science and machine learning.

Communicationsss

Bayesian optimisation: What it is, and how it can improve modelling

Tue, 27th Jul 2021
Originally used to break free from the grid, Bayesian optimisation efficiently uncovers the global maxima of a black-box function in a defined parameter space.