<prompt> Hlalosa mekhoa e meli ea ho shebella sebopeho sa ka hare sa neural network.nan  <response>: Instruction in English: Identify two techniques to observe a neural networks internal structure. . Response in English: There are multiple techniques to observe a neural networks internal structure. Here are two such methods:1. Activation Visualization: This technique involves analyzing the neural networks inner functioning by visualizing the activation outputs of different layers in the model. This helps in understanding how the data flows through the layers and how the neural network processes it to make predictions. Many visualization tools are available for this purpose, which can display a heat map of the activations for chosen neurons.2. Weights and Bias Analysis: The weights and biases form the essential connecting units between different layers in a neural network, and analyzing their values can provide insights into the model structure. For instance, observing the changing trends of the weights in the training period could indicate if the model is overfitting or if the learning rate is too high. Similarly, analyzing the bias values can give insights into the symmetry properties of the neural network. . Response in Sesotho: Ho na le mekhoa e mengata ea ho bona sebopeho sa ka hare sa neural network. Mekhoa e meli ea mofuta ona ke ena: 1. Activation Visualization: Mokhoa ona o kenyelletsa ho hlahloba tsebetso e ka hare ea marang-rang a neural ka ho bona ka mahlo liphetho tsa tsebetso ea mekhahlelo e fapaneng ea mohlala. Sena se thusa ho utloisisa hore na data e phalla joang ka hara mekhahlelo le hore na marang-rang a neural a e sebetsa joang ho etsa likhakanyo. Lisebelisoa tse ngata tsa pono li teng molemong ona, tse ka bontsang mapa oa mocheso oa li-activation bakeng sa li-neurons tse khethiloeng. 2. Tlhahlobo ea Boima le Leeme: Boima le litšekamelo li theha likarolo tsa bohlokoa tsa ho hokahanya pakeng tsa lihlopha tse fapaneng tsa marang-rang a methapo ea kutlo, me ho hlahloba litekanyetso tsa bona ho ka fana ka lintlha tse mabapi le sebopeho sa mohlala. Ka mohlala, ho shebella ho fetoha ha litekanyo nakong ea koetliso ho ka bontša hore na mohlala o fetelletse kapa haeba tekanyo ea ho ithuta e phahame haholo. Ka mokhoa o tsoanang, ho hlahloba litekanyetso tsa leeme ho ka fana ka leseli mabapi le thepa ea symmetry ea neural network. 