5 Machine Learning for IoT
313
4. A. Smola, S.V.N. Vishwanathan, Introduction to Machine Learning (Cambridge University
Press, Cambridge, 2008)
5. A. Smola, S. Vishwanathan, Introduction to Machine Learning, vol 32 (Cambridge University,
Cambridge, 2008), p. 34
6. H. Zou, T. Hastie, Regularization and variable selection via the elastic net. J. R. Stat. Soc.
67(2), 301–320 (2005)
7. O. Sosnovshchenko, O. Baiev, Machine Learning with Swift: Artificial Intelligence for IOS
(Packt Publishing Ltd, 2018). https://www.amazon.com/Machine-Learning-Swift-ArtificialIntelligence/dp/1787121518.
8. Stanford Machine Learning. Available from: https://see.stanford.edu/Course/CS229.
9. I. Steinwart, A. Christmann, Support Vector Machines (Springer Science & Business Media,
2008). https://link.springer.com/book/10.1007/978-0-387-77242-4#about.
10. SVM (Support Vector Machine)—Theory. Available from: https://medium.com/machinelearning-101/chapter-2-svm-support-vector-machine-theory-f0812effc72.
11. H.H. Aghdam, E.J. Heravi, Guide to Convolutional Neural Networks, vol 10 (Springer, New
York, NY, 2017), pp. 978–973
12. K. Huang, Deep Learning: Fundamentals (Springer, Theory and Applications, 2019). https://
www.springer.com/gp/book/9783030060725#aboutBook.
13. A. Carvalhal, T. Ribeiro, Do artificial neural networks provide better forecasts? Evidence from
Latin American stock indexes. Lat. Am. Bus. Rev. 8(3), 92–110 (2008)
14. Basic Overview of Convolutional Neural Network (CNN). Available from: https:/
/medium.com/@udemeudofia01/basic-overview-of-convolutional-neural-network-cnn4fcc7dbb4f17.
15. A. Krizhevsky, I. Sutskever, G.E. Hinton, Imagenet classification with deep convolutional
neural networks. in Advances in Neural Information Processing Systems, (2012), pp. 1097–
1105.
16. Convolutional Neural Networks. Available from: https://medium.com/machine-learning-bites/
deeplearning-series-convolutional-neural-networks-a9c2f2ee1524.
313
4. A. Smola, S.V.N. Vishwanathan, Introduction to Machine Learning (Cambridge University
Press, Cambridge, 2008)
5. A. Smola, S. Vishwanathan, Introduction to Machine Learning, vol 32 (Cambridge University,
Cambridge, 2008), p. 34
6. H. Zou, T. Hastie, Regularization and variable selection via the elastic net. J. R. Stat. Soc.
67(2), 301–320 (2005)
7. O. Sosnovshchenko, O. Baiev, Machine Learning with Swift: Artificial Intelligence for IOS
(Packt Publishing Ltd, 2018). https://www.amazon.com/Machine-Learning-Swift-ArtificialIntelligence/dp/1787121518.
8. Stanford Machine Learning. Available from: https://see.stanford.edu/Course/CS229.
9. I. Steinwart, A. Christmann, Support Vector Machines (Springer Science & Business Media,
2008). https://link.springer.com/book/10.1007/978-0-387-77242-4#about.
10. SVM (Support Vector Machine)—Theory. Available from: https://medium.com/machinelearning-101/chapter-2-svm-support-vector-machine-theory-f0812effc72.
11. H.H. Aghdam, E.J. Heravi, Guide to Convolutional Neural Networks, vol 10 (Springer, New
York, NY, 2017), pp. 978–973
12. K. Huang, Deep Learning: Fundamentals (Springer, Theory and Applications, 2019). https://
www.springer.com/gp/book/9783030060725#aboutBook.
13. A. Carvalhal, T. Ribeiro, Do artificial neural networks provide better forecasts? Evidence from
Latin American stock indexes. Lat. Am. Bus. Rev. 8(3), 92–110 (2008)
14. Basic Overview of Convolutional Neural Network (CNN). Available from: https:/
/medium.com/@udemeudofia01/basic-overview-of-convolutional-neural-network-cnn4fcc7dbb4f17.
15. A. Krizhevsky, I. Sutskever, G.E. Hinton, Imagenet classification with deep convolutional
neural networks. in Advances in Neural Information Processing Systems, (2012), pp. 1097–
1105.
16. Convolutional Neural Networks. Available from: https://medium.com/machine-learning-bites/
deeplearning-series-convolutional-neural-networks-a9c2f2ee1524.