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portada Cracking the Machine Learning Code: Technicality or Innovation?
Type
Physical Book
Collection
Studies in Computational Intelligence
Year
2025
Pages
127
Format
Paperback
Dimensions
23.50 x 15.50 cm
ISBN13
9789819727223

Cracking the Machine Learning Code: Technicality or Innovation?

Kc Santosh;Siddhi K. Bajracharya;Rodrigue Rizk (Author) · Springer Nature · Paperback

Cracking the Machine Learning Code: Technicality or Innovation? - KC Santosh;Siddhi K. Bajracharya;Rodrigue Rizk

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Synopsis "Cracking the Machine Learning Code: Technicality or Innovation?"

It typically includes model selection, parameter tuning and optimization, use of pre-trained models and transfer learning, right use of limited data, model interpretability and explainability, feature engineering and autoML robustness and security, and computational cost – efficiency and scalability.

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