<prompt> Sisinya mekhoa e 5 ho lokisa lintlha tsa ho ithuta ka mochini.ha ho letho  <response>: Instruction in English: Suggest 5 practices to prepare data for machine learning. . Response in English: 1. Data Cleaning: Data cleaning is the process of identifying and removing or correcting inaccurate records from a dataset, table, or database. This helps ensure that the data is accurate and ready for machine learning.2. Data Transformation: This involves converting data into a format that is more suitable for machine learning. Examples of data transformation include converting categorical data into numerical data, normalizing data, and scaling data.3. Data Integration: This involves combining data from multiple sources into a single, cohesive data set. This can be done through processes such as data merging, data concatenation, and data joining.4. Feature Engineering: This involves creating new features or modifying existing features to improve the performance of machine learning models. Feature engineering can involve the aggregation of data, splitting up data into multiple columns, or creating new columns based on existing data.5. Data Reduction: This involves reducing the size of the data set to make it easier to analyze and process. This can be done through methods such as dimensionality reduction, feature selection, and data sampling. . Response in Sesotho: 1. Tlhoekiso ea Boitsebiso: Ho hloekisa boitsebiso ke mokhoa oa ho khetholla le ho tlosa kapa ho lokisa litlaleho tse sa nepahalang ho tswa ho dataset, tafole kapa database. Sena se thusa ho netefatsa hore data e nepahetse ebile e loketse ho ithuta ka mochini. 2. Phetoho ea Boitsebiso: Sena se kenyelletsa ho fetola boitsebiso ka mokhoa o loketseng haholoanyane ho ithuta mochine. Mehlala ea phetoho ea data e kenyelletsa ho fetolela data ea likarolo hore e be lintlha tsa linomoro, data e tloaelehileng, le ho lekanya lintlha. 3. Tšebeliso ea Boitsebiso: Sena se kenyelletsa ho kopanya lintlha tse tsoang mehloling e mengata ho ea sebakeng se le seng, se kopantsoeng sa data. Sena se ka etsoa ka mekhoa e kang ho kopanya data, ho kopanya data, le ho kopanya data. 4. Boenjineri ba Tšobotsi: Sena se kenyelletsa ho theha likarolo tse ncha kapa ho fetola likarolo tse teng ho ntlafatsa tsebetso ea mefuta ea ho ithuta ea mochini. Boenjineri ba likarolo bo ka kenyelletsa ho bokellana ha data, ho arola lintlha ka likholomo tse ngata, kapa ho theha likholomo tse ncha ho latela lintlha tse teng. 5. Phokotso ea Lintlha: Sena se kenyelletsa ho fokotsa boholo ba data e behiloeng ho etsa hore ho be bonolo ho e hlahloba le ho e sebetsa. Sena se ka etsoa ka mekhoa e kang ho fokotsa boholo, khetho ea likarolo, le sampole ea data. 