In this short video we will discuss the difference between parameters vs hyperparameters in machine learning. Parameters is something that a machine learning model trains and figure out such as weights and bias for the model. Hyper parameter on the other end is something you manually specify such as number of hidden layers, neurons in each hidden layer, epochs etc.
Do you want to learn technology from me? Check https://codebasics.io/ for my affordable video courses.
๐ Website: https://www.codebasics.io/
Codebasics Hindi channel: https://www.youtube.com/channel/UCTmFBhuhMibVoSfYom1uXEg
#๏ธโฃ Social Media #๏ธโฃ
๐ Discord: https://discord.gg/r42Kbuk
๐ธ Instagram: https://www.instagram.com/codebasicshub/
๐ Facebook: https://www.facebook.com/codebasicshub
๐ฑ Twitter: https://twitter.com/codebasicshub
๐ Linkedin: https://www.linkedin.com/company/codebasics/
โโ DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers’.
source




