Скачать с ютуб Machine Learning Project - 6. Tune and Improve - ML model; Hyperparameters | Practice & Theory в хорошем качестве

Machine Learning Project - 6. Tune and Improve - ML model; Hyperparameters | Practice & Theory

This video tutorial shows how to improve model predictions through experiments (Hyperparameter Tuning). Manual hyperparameter tuning and Hyperparameter tuning using: RandomizedSearchCV and GridSearchCV. The unique part is in reusing the same ML Workflow to tune & improve different models - just changing hyperparameter for ML model, and rerun! Covered with theory and practical coding examples using pandas and scikit-learn. It can be used as a standalone video tutorial or as a part of bigger picture of Machine Learning Workflow - https://machinelearningmaverick.com/2... Happy Coding! More useful content can be found on my YouTube Channel    / @machinelearningmaverick   and on my blog https://machinelearningmaverick.com/ #ml #machinelearning #jupyter #jupyternotebook #python #pandas #scikitlearn #datascience #machinelearningengineer #tune #improve #randomizedsearchcv #gridsearchcv #hyperparameters #manually #corssvalidation #randomforest #randomforestregressor #machinelearningmaverick The video was intentionally recorded slowly and calmly so that everyone could follow my message. 𝐓𝐡𝐨𝐬𝐞 𝐰𝐡𝐨 𝐧𝐞𝐞𝐝 𝐦𝐨𝐫𝐞 𝐝𝐲𝐧𝐚𝐦𝐢𝐜𝐬 𝐜𝐚𝐧 𝐬𝐩𝐞𝐞𝐝 𝐮𝐩 𝐭𝐡𝐞 𝐯𝐢𝐝𝐞𝐨 𝟏.𝟓𝐱 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐥𝐨𝐬𝐢𝐧𝐠 𝐭𝐡𝐞 𝐦𝐚𝐭𝐞𝐫𝐢𝐚𝐥 :)