Machine learning methods studied

The next joint scientific seminar "Machine learning methods " was held at the Institute of Information Technology of ANAS.

The employee of Department No.1 Adila Imamverdiyeva gave detailed information on the main issues of machine learning, application areas, various machine learning methods.

Speaking about the history of machine learning, A. Imamverdiyeva noted that for the first time in 1959 the name was coined by Arthur Samuel. The lecturer explained in details the classification, clustering and regression issues of machine learning.

She stressed that machine learning is a multidisciplinary field. It interconnected with Machine learning includes mathematical statistics, computer science, applied mathematics, psychology, physiology, and so on. Machine learning algorithms and methods include Decision Tree, k-Near Neighbor, SVM-Support Vector Machine, Bayes Networks, Neural Networks, she said.

The methods of machine learning methods include data collection, data processing, data analysis, training and testing.

Machine learning algorithms are used in a wide variety of application: Computer Vision, Speech Recognition, Image Recognition, Natural Language Processing, Information Retrieval and etc.

She talked about classification and clustering issues that form the basis of machine learning. 

A. Imamverdiyeva gave detailed information about classification algorithms: k-Fold Cross Validation, Confusion Matrix, k-nearest neighbor, SVM-support vector machine and etc. 

Views on presentation were exchanged and questions were answered.

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