<prompt> Hlalosa hore na mohlala oa ho ithuta ka mochini o ka sebelisoa joang ho lemoha mongolo.nan  <response>: Instruction in English: Explain how a machine learning model can be used to recognize handwriting. . Response in English: Machine learning is a type of Artificial Intelligence AI that enables software applications to predict outcomes without explicit programming. One of its many applications is in the recognition of handwriting.To recognize handwriting, a machine learning model must be trained on a large dataset of handwriting samples. The dataset usually consists of images of handwritten characters or words, along with their corresponding transcriptions labels. The model then learns to recognize patterns and unique features in the images, such as the shapes and strokes of the characters, allowing it to associate the images with their corresponding labels.There are a variety of machine learning algorithms that can be used for handwriting recognition, one of the most popular being the convolutional neural network CNN. CNNs are particularly good at image classification tasks and can automatically learn and extract features from images that are useful for classification. These features could include, for instance, the slope of a line, the presence of a loop, or the angle of intersection between lines.During the training phase, the machine learning model processes the images and their labels, adjusting its internal parameters to improve its accuracy. Once the training is complete, the model can then be used to recognize new handwriting samples. When presented with a new image, the model analyzes its features based on what it has learned during training and outputs its prediction for the label of the image.In summary, a machine learning model can be used to recognize handwriting by being trained on a large dataset of handwriting samples, learning to recognize patterns and features unique to handwriting, and then using that knowledge to make predictions on new, unseen handwriting samples. . Response in Sesotho: Ho ithuta ka mochini ke mofuta oa Artificial Intelligence AI e nolofalletsang litsebetso tsa software ho bolela esale pele sephetho ntle le mananeo a hlakileng. E ngoe ea litsebetso tsa eona tse ngata ke temohong ea mongolo. Ho lemoha mongolo, mofuta oa ho ithuta ka mochini o tlameha ho koetlisoa ka pokello ea lintlha tse kholo tsa lisampole tsa ho ngola ka letsoho. Lethathamo hangata le na le litšoantšo tsa litlhaku tse ngotsoeng ka letsoho kapa mantsoe, hammoho le lingoliloeng tse tsamaellanang le tsona li-labels. Joale mohlala o ithuta ho lemoha mekhoa le likarolo tse ikhethang litšoantšong, tse kang libopeho le liropo tsa litlhaku, ho li lumella ho amahanya litšoantšo le mangolo a tsona a lumellanang. Ho na le mekhoa e fapaneng ea ho ithuta ka mochini e ka sebelisoang bakeng sa temoho ea mongolo, e ngoe ea tse tsebahalang haholo ke convolutional neural network CNN. Li-CNN li sebetsa hantle haholo mesebetsing ea ho arola litšoantšo me li ka ithuta le ho ntša likarolo ho tsoa litšoantšong tse thusang ho arola. Likarolo tsena li ka kenyelletsa, mohlala, moepa oa mola, boteng ba loop, kapa angle ea mateano lipakeng tsa mela. Nakong ea mohato oa koetliso, mohlala oa ho ithuta mochine o sebetsana le litšoantšo le lileibole tsa bona, o fetola likarolo tsa oona tse ka hare ho ntlafatsa ho nepahala ha oona. Hang ha lithupelo li felile, mohlala o ka sebelisoa ho lemoha lisampole tse ncha tsa mongolo. Ha e hlahisoa ka setšoantšo se secha, mohlala o hlahlobisisa likarolo tsa oona ho latela seo o ithutileng sona nakong ea koetliso me o hlahisa tlhahiso ea oona bakeng sa leibole ea setšoantšo. Ka bokhutsoanyane, mokhoa oa ho ithuta ka mochini o ka sebelisoa ho lemoha mongolo ka ho koetlisoa ka pokello ea data e kholo ea disampole tsa ho ngola, ho ithuta ho lemoha mekhoa le likarolo tse ikhethang ka ho ngola ka letsoho, le ho sebelisa tsebo eo ho etsa likhakanyo ka lisampole tse ncha, tse sa bonahaleng tsa ho ngola. 