Скачать с ютуб Bagging/Bootstrap Aggregating in Machine Learning with examples в хорошем качестве

Bagging/Bootstrap Aggregating in Machine Learning with examples

00:00 – Intro 00:16 – Bagging/Bootstrap 02:28 – Ensemble learning Bagging, short for Bootstrap Aggregating, is an ensemble learning technique used to improve the stability and accuracy of machine learning models by reducing variance. It involves creating multiple versions of a predictor and using these to get an aggregated result. 👉Subscribe to our new channel:   / @varunainashots   Other subject playlist Link: -------------------------------------------------------------------------------------------------------------------------------------- ►Theory of Computation    • TOC(Theory of Computation)   ►Operating System:    • Operating System (Complete Playlist)   ►Database Management System:    • DBMS (Database Management system) Com...   ►Computer Networks:    • Computer Networks (Complete Playlist)   ►Artificial Intelligence:    • Artificial Intelligence (Complete Pla...   ►Computer Architecture:    • Computer Organization and Architectur...   ►Design and Analysis of algorithms (DAA):    • Design and Analysis of algorithms (DAA)   ►Structured Query Language (SQL):    • Structured Query Language (SQL)   --------------------------------------------------------------------------------------------------------------------------------------- Our Social Media: ► Subscribe us on YouTube-   / gatesmashers   ► Like Our page on Facebook -   / gatesmashers   ► Follow us on Instagram-  / gate.smashers   -------------------------------------------------------------------------------------------------------------------------------------- ►A small donation would help us continue making GREAT Lectures for you. ►Be a Member & Give your Support on bellow link :    / @gatesmashers   ►UPI: gatesmashers@apl ►Paypal Account: paypal.me/GSmashers ►For any other Contribution like notes pdfs, feedback, suggestion etc [email protected] ►For Bussiness Query [email protected]