Elektron xabarlarda spamni aniqlash va tasniflash


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  1. Aurelian Geron, Hands on Machine Learning with Scikit-Learn Keras&Tensorflow // Second edition Concepts, Tools, and Techniques to Build Intelligent Systems, 2019, 510 pages

  2. Oliver Theobald, “Machine Learning for Absolute Beginners”, second edition, 2017, 128 pages

  3. Жуков Л.А., Решетникова Н.В. Приложения нейронных сетей: Учебное пособие для студентов, учащихся лицея и ЗПШНИ / Л. А. Жуков, Н. В. Решетникова. Красноярск: ИПЦ КГТУ, 2007. 154 с.

  4. Stanford course CS231n on “Convolutional Neural Networks for Visual Recognition”

  5. Heidelberg, S. B. (2005). Introduction to Machine Learning Using Neural Nets. Retrieved on 9/02/2015 from http://link.springer.com/chapter/10.1007/3-540-27335-2_7

  6. Carreras, X., & Marquez, L. (2001). Boosting trees for anti-spam email filtering. In Proceedings of the Conference on Recent Advances in Natural Language Processing (RANLP-01), Tzigov Chark, Bulgaria (pp. 12-14).

  7. Mitchell, T., & Chen, L. (2003). Learning to filter spam e-mail: A comparison of a naive Bayesian and a memory-based approach. In Proceedings of the AAAI-2003 Workshop on Learning for Text Categorization (Vol. 1, pp. 27-30).

  8. Tjøstheim, I., & Kvellestad, T. (2004). Email classification using support vector machines. In Proceedings of the Fourth International Conference on Intelligent Data Engineering and Automated Learning (pp. 674-681). Springer.

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