107,92 €
143,89 €
Kaina su kodu: ENG
Applied Machine Learning
Applied Machine Learning
107,92 €
143,89 €
  • Išsiųsime per 10–14 d.d.
1. Learning to Classify.- 2. SVM's and Random Forests.- 3. A Little Learning Theory.- 4. High-dimensional Data.- 5. Principal Component Analysis.- 6. Low Rank Approximations.- 7. Canonical Correlation Analysis.- 8. Clustering.- 9. Clustering using Probability Models.- 10. Regression.- 11. Regression: Choosing and Managing Models.- 12. Boosting.- 13. Hidden Markov Models.- 14. Learning Sequence Models Discriminatively.- 15. Mean Field Inference.- 16. Simple Neural Networks.- 17. Simple Image Cl…
  • Kaina galioja įvedus kodą: ENG

Applied Machine Learning (el. knyga) (skaityta knyga) | knygos.lt

Atsiliepimai

(3.33 Goodreads įvertinimas)
Įvertink ir tu! Visi atsiliepimai

Aprašymas

1. Learning to Classify.- 2. SVM's and Random Forests.- 3. A Little Learning Theory.- 4. High-dimensional Data.- 5. Principal Component Analysis.- 6. Low Rank Approximations.- 7. Canonical Correlation Analysis.- 8. Clustering.- 9. Clustering using Probability Models.- 10. Regression.- 11. Regression: Choosing and Managing Models.- 12. Boosting.- 13. Hidden Markov Models.- 14. Learning Sequence Models Discriminatively.- 15. Mean Field Inference.- 16. Simple Neural Networks.- 17. Simple Image Classi¿ers.- 18. Classifying Images and Detecting Objects.- 19. Small Codes for Big Signals.- Index.

NEMOKAMAS PRISTATYMAS

Kaina galioja įvedus kodą: ENG

107,92 €
143,89 €
Išsiųsime per 10–14 d.d.

Akcija baigiasi už 1d.09:50:10

Nuolaidos kodas galioja perkant nuo 5 €. Nuolaidos nesumuojamos.

Prisijunkite ir už šią prekę
gausite 1,44 Knygų Eurų!?
Įsigykite dovanų kuponą
Daugiau

1. Learning to Classify.- 2. SVM's and Random Forests.- 3. A Little Learning Theory.- 4. High-dimensional Data.- 5. Principal Component Analysis.- 6. Low Rank Approximations.- 7. Canonical Correlation Analysis.- 8. Clustering.- 9. Clustering using Probability Models.- 10. Regression.- 11. Regression: Choosing and Managing Models.- 12. Boosting.- 13. Hidden Markov Models.- 14. Learning Sequence Models Discriminatively.- 15. Mean Field Inference.- 16. Simple Neural Networks.- 17. Simple Image Classi¿ers.- 18. Classifying Images and Detecting Objects.- 19. Small Codes for Big Signals.- Index.

Atsiliepimai

  • Atsiliepimų nėra
0 pirkėjai įvertino šią prekę.
5
0%
4
0%
3
0%
2
0%
1
0%
(rodomas nebus)
Knygos.lt komentarų taisyklės
[{"option":"198","probability":1,"style":{"backgroundColor":"#f2f2f2"},"image":{"uri":"\/uploads\/images\/wheel_of_fortune\/69ba4d2eb09811773817134.png","sizeMultiplier":0.6,"landscape":true,"offsetX":-50}},{"option":"197","probability":1.3,"style":{"backgroundColor":"#dc3743"},"image":{"uri":"\/uploads\/images\/wheel_of_fortune\/69ba4d162418a1773817110.png","sizeMultiplier":0.6,"landscape":true,"offsetX":-50}},{"option":"196","probability":1.6,"style":{"backgroundColor":"#f2f2f2"},"image":{"uri":"\/uploads\/images\/wheel_of_fortune\/69ba4cfe204071773817086.png","sizeMultiplier":0.6,"landscape":true,"offsetX":-50}},{"option":"195","probability":1.5,"style":{"backgroundColor":"#dc3743"},"image":{"uri":"\/uploads\/images\/wheel_of_fortune\/69ba4ce1bac331773817057.png","sizeMultiplier":0.6,"landscape":true,"offsetX":-50}},{"option":"194","probability":1.5,"style":{"backgroundColor":"#f2f2f2"},"image":{"uri":"\/uploads\/images\/wheel_of_fortune\/69ba4ca477abe1773816996.png","sizeMultiplier":0.6,"landscape":true,"offsetX":-50}},{"option":"193","probability":1.6,"style":{"backgroundColor":"#dc3743"},"image":{"uri":"\/uploads\/images\/wheel_of_fortune\/69ba4c8f03fd21773816975.png","sizeMultiplier":0.6,"landscape":true,"offsetX":-50}},{"option":"192","probability":1.4,"style":{"backgroundColor":"#f2f2f2"},"image":{"uri":"\/uploads\/images\/wheel_of_fortune\/69ba4c6fa50cc1773816943.png","sizeMultiplier":0.6,"landscape":true,"offsetX":-50}},{"option":"191","probability":0.1,"style":{"backgroundColor":"#ffeb00"},"image":{"uri":"\/uploads\/images\/wheel_of_fortune\/69ba4c4a296b81773816906.png","sizeMultiplier":0.6,"landscape":true,"offsetX":-50}}]