https://atrc.net.pk/dokuwiki/ 2026-04-29T08:51:22+00:00 https://atrc.net.pk/dokuwiki/ https://atrc.net.pk/dokuwiki/lib/tpl/dokuwiki/images/favicon.ico text/html 2022-04-26T09:19:00+00:00 Anonymous (anonymous@undisclosed.example.com) https://atrc.net.pk/dokuwiki/doku.php?id=products:ict:ai:machine_learning:hyperparameter_tuning&rev=1650964740&do=diff <https://www.analyticsvidhya.com/blog/2021/04/evaluating-machine-learning-models-hyperparameter-tuning/> Evaluating Machine Learning Models using Hyperparameter Tuning <https://www.jeremyjordan.me/hyperparameter-tuning/> Hyperparameter tuning for machine learning models. <https://cloud.google.com/ai-platform/training/docs/hyperparameter-tuning-overview> Overview of hyperparameter tuning <https://en.wikipedia.org/wiki/Hyperparameter_optimization> Hyperparameter optimization <https://nept… text/html 2022-04-26T09:19:00+00:00 Anonymous (anonymous@undisclosed.example.com) https://atrc.net.pk/dokuwiki/doku.php?id=products:ict:ai:machine_learning:ml_pipelines&rev=1650964740&do=diff <https://www.datarobot.com/blog/what-a-machine-learning-pipeline-is-and-why-its-important/> What a Machine Learning Pipeline is and Why It’s Important <https://databricks.com/glossary/what-are-ml-pipelines> ML Pipelines Typically when running machine learning algorithms, it involves a sequence of tasks including pre-processing, feature extraction, model fitting, and validation stages. For example, when classifying text documents might involve text segmentation and cleaning, extracting featur… text/html 2022-04-26T09:19:00+00:00 Anonymous (anonymous@undisclosed.example.com) https://atrc.net.pk/dokuwiki/doku.php?id=products:ict:ai:machine_learning:mlops&rev=1650964740&do=diff MLOps MLOps or ML Ops is a set of practices that aims to deploy and maintain machine learning models in production reliably and efficiently.[1] The word is a compound of “machine learning” and the continuous development practice of DevOps in the software field. Machine learning models are tested and developed in isolated experimental systems. When an algorithm is ready to be launched, MLOps is practiced between Data Scientists, DevOps, and Machine Learning engineers to transition the algorithm …