Alihan Zihna

A Review of Hyperparameter Optimization Frameworks on Python

Hyperparameter optimization is the process of finding the optimum values that control the learning process for a machine learning algorithm. This can span from a single regularization value for logistic regression to searching for optimal architectures in a Neural Network. It is also arguably one of the most time-consuming operations that can easily take days or weeks. In this talk, we'll take a look at the common ways and recent developments to perform this crucial step and compare some of the open-source options that exist in the Python ecosystem. This is a beginner to intermediate level talk that will cover some basics.

Mini bio: Data Scientist at CKDelta. Ex-Mechanical Engineer with MSc in Industrial Engineering. He was a Lindy Hop instructor before COVID times.

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