Exploring Optimization Algorithms in Machine Learning: From Theory to Practice

by kinky

Optimization algorithms in machine learning bridge theoretical foundations with practical applications, crucial for refining model performance. Techniques like gradient descent, stochastic gradient descent (SGD), and advanced methods such as Adam and RMSprop optimize model parameters to minimize error and enhance accuracy. Theoretical understanding encompasses concepts like convexity, convergence criteria, and adaptive learning rates, essential for...

• Format: Paperback
• Language: English
• ISBN: 3384275837
• ISBN13: 9783384275837
• Release Date: July 2024
• Publisher: Tredition Gmbh
• Length: 340 Pages
• Weight: 1.10 lbs.
• Dimensions: 0.8" x 6.0" x 9.0"