
Information-Driven Machine Learning
This groundbreaking book transcends traditional machine learning approaches by introducing information measurement methodologies that revolutionize the field.
Stemming from a UC Berkeley seminar on experimental design for machine learning tasks, these techniques aim to overcome the ''black box'' approach of machine learning by reducing conjectures such as magic numbers (hyper-parameters) or model-t...
This groundbreaking book transcends traditional machine learning approaches by introducing information measurement methodologies that revolutionize the field.
Stemming from a UC Berkeley seminar on experimental design for machine learning tasks, these techniques aim to overcome the ''black box'' approach of machine learning by reducing conjectures such as magic numbers (hyper-parameters) or model-t...