Data processing algorithm in machine learning

Author: Gurami Asanishvili
Keywords: Machine learning, Data processing, Algorithms, Data processing algorithms
Annotation:

The main purpose of machine learning is to create a model from input and output quantities, state of training set which will be used to solve some kind of problems Intelligence systems are based on machine learning Therefore it’s important to create an adequate model.Such kind of systems might be based on some kind of information. There exists a lot of different algorithms which are used for such systems, for example: Classification, Clustering. As usual if they are used separately, it does not affect high performance. It appears from this we have to combine/merge such kind of algorithms In any case it’s required to define these important questions: Input and output information, the main processes and principles of whole system. It’s important to define input information adequately for every used algorithm. There exists many kind of intelligence system, therefore input information might be defined in any format. There exists many kind of information, therefore it may be: String based, Number based and etc. As usual intelligence systems are based on two kinds of information: Quantitative and Qualitative. for this machine learning to use several types of algorithm that help us process data and then use them to more quickly analyze them. in this lecture one of the algorithms of machine learning which helps us to process the data will be discussed.

Lecture files:

მანქანური სწავლების მონაცემთა დამუშავების ალგორითმი [ka]