Exploring Optimization Algorithms in Machine Learning: From Theory to Practice

Name: Exploring Optimization Algorithms in Machine Learning: From Theory to Practice
Brand: tredition
SKU: 9783384275837
Price: 19.42 EUR
Availability: InStock

Автор: Kinky

Език:

Корици: С меки корици

Издател: tredition

Наличност: Външен склад

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Optimization algorithms in machine learning bridge theoretical foundations with practical applicatio...

Информация за книгата

Автор

Kinky

Език

Английски език

Корици

Книга - С меки корици

Издадена

2024

страници

340

EAN

9783384275837

ISBN

3384275837

Enbook ID

46199574

Издател

tredition

Теглоt

576

Размери

155 x 234 x 24

Пълно описание

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.

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Exploring Optimization Algorithms in Machine Learning: From Theory to Practice

Информация за книгата

Пълно описание

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Клиенти, които купиха тази книга, купиха също