Bagging and Boosting Algorithm | Machine Learning Techniques
HTML-код
- Опубликовано: 13 сен 2024
- Bagging: A technique that reduces variance by training multiple models independently on different random subsets of the data and then averaging their predictions.
Boosting: A technique that reduces bias by sequentially training models, each focusing on correcting the errors made by the previous models, and then combining their predictions.
==========================================================
Join this channel to get access to perks:
/ @myowncampus
==========================================================
Checkout our Other Playlists
==========================================================
Statistics For Data Science 2
• Statistics For Data Sc...
Linear Algebra
• Linear Algebra
Machine Learning Foundation
• Machine Learning Found...
Multivariable Calculus:
• Multivariable Calculus
Mathematics 2 for Data Science : • Mathematics For Data S...
Mathematics 1 for Data Science : • Mathematics For data s...
Python OPPE PYQ playlist : • PYTHON OPPE 1 PYQ QUES...
Python Sessions : • Playlist
==========================================================
ABOUT OUR CHANNEL
Our channel is about teaching and exploring. We cover lots of cool stuff, such as Data science, Machine learning and Coding
Check out our channel here:
/ data_matrix
Don’t forget to subscribe!
==========================================================
GET IN TOUCH
Contact us on Rishu24oct@gmail.com
==========================================================
FOLLOW US ON SOCIAL
Get updates or reach out to Get updates on our social media profiles!
Facebook: / rishu.rajgautam56
Instagram: / rishu_raj_gautam
LinkedIn: / rishurajgautam
BRO PYQ papers please😭😭😭