<prompt> Hlalosa phapang lipakeng tsa marang-rang a neural a sa tebang le netweke e tebileng ea methapo.nan  <response>: Instruction in English: Describe the differences between a shallow neural network and a deep neural network. . Response in English: A neural network is a type of artificial intelligence model that mimics the functioning of the human brain in processing data and recognizing patterns. There are two types of neural networks: shallow neural networks and deep neural networks. Here are some of the key differences between the two:1. Number of Hidden Layers:The main architectural difference between a shallow neural network and a deep neural network is the number of hidden layers. A shallow neural network has one hidden layer, while a deep neural network has multiple hidden layers.2. Complexity:Deep neural networks are more complex than shallow neural networks because they have a higher number of hidden layers with many more parameters. This makes deep neural networks better equipped to handle more difficult computational problems than shallow neural networks.3. Representational Power:The multiple layers in a deep neural network allow it to learn increasingly abstract or detailed features from the data, which enhances its representational power. On the other hand, a shallow neural network might not be able to represent much complex relationships among the features.4. Learning Features:A deep neural network is designed to learn different levels of features, with each layer learning a different set of features. In contrast, a shallow neural network learns all of its features together and hence might not be able to differentiate between them effectively.5. Training:Training a deep neural network is generally more challenging than training a shallow neural network. This is because the increased number of layers and parameters in a deep neural network might result in overfitting or getting stuck in local minima. Special techniques such as dropout or batch normalization are often used to train deep neural networks effectively.Overall, deep neural networks provide a more powerful model than shallow neural networks but require more time, resources, and expertise to train effectively. . Response in Sesotho: Neural network ke mofuta oa bohlale ba maiketsetso bo etsisang tsebetso ea boko ba motho ho sebetsana le data le ho lemoha mekhoa. Ho na le mefuta e meli ea li-neural network: shallow neural networks le deep neural network. Mona ke tse ling tsa liphapang tse ka sehloohong pakeng tsa tse peli: 1. Palo ea Lithako tse Patehileng: Phapang e ka sehloohong ea meralo pakeng tsa marang-rang a sa tebang a neural le neural network e tebileng ke palo ea lihlopha tse patiloeng. Neural network e sa tebang e na le lera le le leng le patiloeng, athe neural network e tebileng e na le likarolo tse ngata tse patiloeng. 2. Ho rarahana: Li-neural network tse tebileng li rarahane ho feta li-neural network tse sa tebang hobane li na le palo e phahameng ea lihlopha tse patehileng tse nang le li-parameter tse ling tse ngata. Sena se etsa hore marang-rang a tebileng a neural a hlomeletsoe hamolemo ho sebetsana le mathata a thata a khomphutha ho feta marang-rang a sa tebang a neural. 3. Matla a Boemeli: Likarolo tse ngata ka hara marang-rang a tebileng a methapo e lumella hore e ithute ka ho eketsehileng likarolo tse sa bonahaleng kapa tse qaqileng ho tsoa ho data, e leng ho matlafatsang matla a eona a boemeli. Ka lehlakoreng le leng, marang-rang a sa tebang a neural a kanna a se khone ho emela likamano tse rarahaneng haholo hara likarolo. 4. Likarolo tsa ho Ithuta: Marang-rang a tebileng a neural a etselitsoe ho ithuta maemo a fapaneng a likarolo, me karolo e ngoe le e ngoe e ithuta sete e fapaneng ea likarolo. Ka lehlakoreng le leng, marang-rang a sa tebang a neural a ithuta likarolo tsohle tsa ona hammoho, kahoo a ka sitoa ho li khetholla ka nepo. 5. Koetliso: Ho koetlisa marang-rang a tebileng a neural hangata ho thata ho feta ho koetlisa marang-rang a sa tebang. Lebaka ke hobane palo e ntseng e eketseha ea lira le li-parameter ho netweke e tebileng ea neural e ka baka ho tlala ho feta tekano kapa ho tsoareha ho minima ea lehae. Mekhoa e ikhethileng e kang ho tlohela mosebetsi kapa ho tloaeleha ha batch hangata e sebelisoa ho koetlisa marang-rang a tebileng a methapo ka katleho. Ka kakaretso, marang-rang a tebileng a neural a fana ka mohlala o matla ho feta marang-rang a sa tebang a neural empa a hloka nako e ngata, lisebelisoa le boiphihlelo ho koetlisa ka katleho. 