Mathematics for Machine Learning /
Contiene: I) Fundamentos matemáticos: 1. Introducción y motivación; 2. Algebra lineal; 3. Geometría analítica; 4. Descomposición de matrices; 5. Cálculo vectorial; 6. Probabilidad y distribuciones; 7. Optimización continua. II) Problemas centrales de aprendizaje automático: 8. Cuando los modelos se...
Kaydedildi:
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| Diğer Yazarlar: | , |
| Materyal Türü: | Kitap |
| Dil: | İngilizce |
| Baskı/Yayın Bilgisi: |
Nueva York, EUA :
Cambridge University,
2021, c2020
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| Konular: | |
| Etiketler: |
Etiket eklenmemiş, İlk siz ekleyin!
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Benzer Materyaller: Mathematics for Machine Learning /
- Linear Algebra and Optimization with Applications to Machine Learning : Fundamentals of Optimization Theory with Applications to Machine Learnig /
- Probabilistic Machine Learning : An Introduction /
- Linear Algebra and Optimization with Applications to Machine Learning : Linear Algebra for Computer Visión, Robotics, and Machine Learning /
- Advanced Engineering Mathematics /
- Bayesian Reasoning and Gaussian Processes for Machine Learning Applications /
- Finite Mathematics for the Managerial, Life, and Social Sciences /