Cracking the Machine Learning Code: Technicality or Innovation?
KC Santosh, Rodrigue Rizk, Siddhi K. Bajracharya
Springer Verlag, Singapore, 2024
185,50 €On orderDelivery: 2-3 weeks
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.
- ISBN-13
- 9789819727193
- ISBN-10
- 9819727197
- Publisher
- Springer Verlag, Singapore
- Year
- 2024
- Publication date
- 2024-05-09
- Pages
- 127
- Dimensions
- 235x155x