<prompt> Akaretsa moeli o moholo ka ho fetisisa oa algorithm ea Neural Network.nan  <response>: Instruction in English: Summarize the biggest limitation of a Neural Network algorithm. . Response in English: One of the biggest limitations of a Neural Network algorithm is its lack of interpretability or its black box nature. This means that it can be difficult to understand how the algorithm arrives at a particular output or prediction, making it hard to explain or justify the results to others. Additionally, Neural Networks can require large amounts of data for training and can take a long time to train, especially for complex tasks. Overfitting can also be a problem, where the model learns to perform well on the training data but not on new, unseen data. . Response in Sesotho: ngoe ea likhaello tse kholo ka ho fetisisa tsa algorithm ea Neural Network ke ho hloka tlhaloso kapa tlhaho ea eona ea lebokose le letšo. Sena se bolela hore ho ka ba thata ho utloisisa hore na algorithm e fihla joang tlhahisong e itseng kapa ho bolela esale pele, ho etsa hore ho be thata ho hlalosa kapa ho lokafatsa liphetho ho ba bang. Ho feta moo, Neural Networks e ka hloka lintlha tse ngata bakeng sa koetliso me e ka nka nako e telele ho koetlisa, haholo-holo bakeng sa mesebetsi e rarahaneng. Overfitting e ka boela ea e-ba bothata, moo mohlala o ithutang ho sebetsa hantle ho data ea koetliso empa eseng ho data e ncha, e sa bonahaleng. 