<prompt> Hlahisa serapa se hlalosang mehato ea ho aha mohlala oa Natural Language Processing NLP.nan  <response>: Instruction in English: Generate a paragraph that explains the steps to build a Natural Language Processing NLP model. . Response in English: To build a Natural Language Processing NLP model, there are several key steps that must be followed. First, you must collect and clean the data that will be used to train the model. This involves removing any irrelevant or redundant information, ensuring that the text is properly formatted, and normalizing the text to ensure consistency. Then, you must preprocess the text data, which involves tokenization, stemming or lemmatization, and the removal of stop words. Next, you must represent the text data numerically using techniques like Bag of Words or Word Embedding. Once the data is in a suitable format, you can choose a machine learning algorithm to train the model, such as Naïve Bayes, Decision Trees, or Neural Networks. Finally, evaluate the performance of the model using metrics like accuracy, precision, recall, and F1 score, and fine-tune the model to improve its performance. . Response in Sesotho: Ho aha mohlala oa Tlhaho ea Puo ea Tlhaho NLP, ho na le mehato e mengata ea bohlokoa e lokelang ho lateloa. Pele, o tlameha ho bokella le ho hloekisa data e tla sebelisoa ho koetlisa mohlala. Sena se kenyelletsa ho tlosa tlhahisoleseding leha e le efe e sa lokelang kapa e sa hlokahaleng, ho netefatsa hore mongolo o hlophisitsoeng hantle, le ho etsa hore mongolo o tloaelehe ho netefatsa ho lumellana. Ebe, o tlameha ho lokisa data ea mongolo esale pele, e kenyelletsang tokenization, stemming kapa lemmatization, le ho tlosoa ha mantsoe a emisang. Ka mora moo, u tlameha ho emela lintlha tsa mongolo ka lipalo u sebelisa mekhoa e kang Mokotla oa Mantsoe kapa ho Embedding ea Lentsoe. Hang ha data e se e le ka mokhoa o loketseng, o ka khetha algorithm ea ho ithuta mochine ho koetlisa mohlala, joalo ka Naïve Bayes, Decision Trees, kapa Neural Networks. Qetellong, lekola tšebetso ea mohlala u sebelisa metrics joalo ka ho nepahala, ho nepahala, ho hopola, le lintlha tsa F1, me u lokise mohlala ho ntlafatsa tsebetso ea ona. 