Browsing by Author "Temirali A."

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    Statistical inference and machine learning in big data
    (Faculty of Engineering and Natural Science, 2019) Temirali A.
    In my practice. I met with different definitions: - Big Data is when data is more than 100GB (500GB. 1TB. who likes it) - Big Data is data that cannot be processed in Excel - Big Data is data that cannot be processed on a single computer. And even such: - Big Data is generally any data. - Big Data does not exist. marketers have invented it. Thus, under Big Data I will understand not some specific amount of data or even the data itself, but their processing methods. which allow distributed information to be processed. These methods cat? be applied both to huge data arrays (such as the content of all pages on the Internet) and to small ones (such as the content of this thesis).
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    USING MACHINE LEARNING CLASSIFICATION ALGORITHMS TO STUDY HOUSE PRICE FOR ALMATY
    (СДУ хабаршысы - 2019, 2019) Zhumabek D. ; Rayev Zh. ; Zhailaubek A. ; Temirali A.
    Abstract. In real estate valuation and house market research, house prices and rental value are generally analyzed by decision tree regression and random forest regression model based on machine learning. Regression model examines the effect of characteristics of goods on their prices. Factors that determine the house prices in Almaty are analyzed in this paper using real dataset from legal site. The most important variables that affect house rents are type of house, type of building, number of rooms, size, and other structural characteristics such as water system, pool, natural gas. Also used jupyter notebook, numpy, pandas, matplotlib, scipy and scikit-learn.