Contact
How to shop
Delivery
Shopping guide
Exploring Optimization Algorithms in Machine Learning: From Theory to Practice
English
48 b
Up to 30 days for returns
Customers also purchased
/
Paperback
60.71
€
/
Hardback
30.90
€
/
Hardback
196.47
€
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 algorithm selection based on dataset characteristics.In practice, implementing these algorithms involves tuning hyperparameters and assessing trade-offs between computational efficiency and model effectiveness across diverse datasets. Recent innovations, including meta-heuristic algorithms like genetic algorithms, further expand optimization capabilities for complex, non-linear problems.Mastering optimization algorithms empowers practitioners to navigate challenges in model training and deployment effectively, ensuring robust performance in real-world applications. This comprehensive understanding supports innovation in machine learning, driving advancements in various fields from healthcare to finance and beyond.
About the book
Give this book today
It's easy
1 Add to cart and choose Deliver as present at the checkout 2 We'll send you a voucher 3 The book will arrive at the recipient's addressYou might also be interested in
/
Paperback
19.20
€
/
Paperback
19.10
€
/
Paperback
9.69
€
/
Paperback
15.50
€
Hi! I'm Libroamiko, your book advisor.
How can I help you?