<prompt> Ha u fuoa dataset, bolela esale pele thekiso ea sehlahisoa X lilemong tse 5 tse tlangLethathamo le nang le litheko tsa lihlahisoa le mekhoa ea thekiso lilemong tse 10 tse fetileng  <response>: Instruction in English: Given a dataset, predict the sales of product X in the next 5 years . Response in English: To predict the sales of product X for the next 5 years, I would need to process and analyze the given dataset containing product prices and sales trends over the past 10 years to identify patterns and relationships between variables. I could use various statistical methods and machine learning algorithms, such as linear regression, decision tree, or Random Forest, to create a predictive model that forecasts future sales. With this model, I could input data for the next 5 years and generate predictions for the sales of product X. It is important to note that the accuracy of the predictions depends on the quality and accuracy of the data provided, and external factors that may not be captured in the dataset could also impact the actual sales performance of the product. . Response in Sesotho: Ho bolela esale pele thekiso ea sehlahisoa X bakeng sa lilemo tse latelang tse 5, ke tla hloka ho sebetsana le ho sekaseka dataset e fanoeng e nang le litheko tsa lihlahisoa le mekhoa ea thekiso lilemong tse 10 tse fetileng ho tseba mekhoa le likamano lipakeng tsa mefuta e fapaneng. Ke ne ke khona ho sebelisa mekhoa e fapaneng ea lipalo-palo le mekhoa ea ho ithuta ka mochini, joalo ka ho fokotseha ha mela, sefate sa liqeto, kapa Random Forest, ho theha mohlala o reriloeng esale pele ka thekiso ea nako e tlang. Ka mohlala ona, ke ne ke khona ho kenya lintlha bakeng sa lilemo tse latelang tsa 5 le ho hlahisa likhakanyo tsa thekiso ea sehlahisoa X. Ke habohlokoa ho hlokomela hore ho nepahala ha lintho tse boletsoeng esale pele ho itšetlehile ka boleng le ho nepahala ha lintlha tse fanoeng, le lintlha tse ka ntle tse ka nang tsa e-ba teng. ho se tsoaroe ho dataset ho ka ama tsebetso ea nete ea thekiso ea sehlahisoa. 