<prompt> Theha sengoloa sa Wikipedia mabapi le thuto e tebileng.nan  <response>: Instruction in English: Create a Wikipedia article about deep learning. . Response in English: Deep learning is a subset of machine learning that utilizes artificial neural networks with multiple layers to model high-level concepts using data. These methods improve upon traditional machine learning techniques by using algorithms, big data, and the computational power of modern processing units to allow computers to learn through experience or training.Deep learning has roots in artificial intelligence research, where researchers first developed the idea of artificial neural networks ANNs in the 1940s. However, it was not until the 1980s that the backpropagation algorithm was developed, allowing ANNs to be trained more effectively. Deep learning has since become a crucial tool for tasks such as computer vision, natural language processing, and speech recognition.At its core, deep learning consists of multiple layers of interconnected nodes or neurons that are organized in a hierarchical manner. Input data is processed layer by layer, with each level of the hierarchy learning more abstract, higher-level features or concepts. For example, when processing an image, the lowest layer may detect edges and contrasts, while higher layers may identify objects or even understand the context of the image.One of the major advantages of deep learning over traditional machine learning techniques is that it can automatically learn the relevant features from raw data, reducing the need for manual feature engineering. Additionally, deep learning algorithms can continually improve their performance through training with large amounts of data.Recent advancements in deep learning have led to breakthroughs in a wide range of applications, such as improving image and speech recognition, enhancing language translation, and advancing drug discovery. Deep learning is also being used to develop autonomous systems, such as self-driving cars, and to improve the performance of traditional artificial intelligence systems, such as game-playing AIs.Despite its many successes, deep learning is not without its challenges. Some of the current areas of research include improving the interpretability of deep learning models, developing new architectures to handle structured data, and improving the robustness of deep learning systems against adversarial attacks.In summary, deep learning is an exciting and rapidly evolving field that has shown great promise in advancing artificial intelligence research and practical applications. As data and computational power continue to grow, it is likely that deep learning will continue to play an important role in the development of new technologies and innovations. . Response in Sesotho: Ho ithuta ka botebo ke karolo e nyane ea ho ithuta ka mochini e sebelisang marang-rang a maiketsetso a marang-rang a nang le likarolo tse ngata ho etsa mohlala oa mehopolo ea boemo bo holimo ka data. Mekhoa ena e ntlafala holima mekhoa ea khale ea ho ithuta mochini ka ho sebelisa li-algorithms, data e kholo, le matla a khomphutha a likarolo tsa sejoale-joale tsa tsebetso ho lumella likhomphutha ho ithuta ka boiphihlelo kapa koetliso. Ho ithuta ho tebileng ho simolohile lipatlisisong tsa bohlale ba maiketsetso, moo bafuputsi ba qalileng ho hlahisa maikutlo a maiketsetso a marang-rang ANNs lilemong tsa bo-1940. Leha ho le joalo, e ne e se ho fihlela lilemong tsa bo-1980 moo algorithm ea backpropagation e ileng ea ntlafatsoa, e lumellang li-ANN ho koetlisoa ka katleho. Ho ithuta ka botebo ho tloha joale e se e le sesebelisoa sa bohlokoa bakeng sa mesebetsi e kang pono ea khomphieutha, tsebetso ea puo ea tlhaho, le temoho ea puo. Motheong oa eona, thuto e tebileng e na le likarolo tse ngata tsa li-node tse hokahaneng kapa neurons tse hlophisitsoeng ka mokhoa oa maemo a holimo. Lintlha tse kentsoeng li sebetsoa ka mekhahlelo, me mohato o mong le o mong oa sehlopha o ithuta likarolo kapa mehopolo ea boemo bo holimo. Ka mohlala, ha o sebetsana le setšoantšo, lera le tlaase ka ho fetisisa le ka lemoha mahlakore le liphapang, ha lihlopha tse phahameng li ka khetholla lintho kapa tsa utloisisa moelelo oa setšoantšo. O mong oa melemo e meholo ea ho ithuta ka botebo ho feta mekhoa ea khale ea ho ithuta mochini ke hore e khona ho ithuta ka bo eona likarolo tse amehang ho tsoa ho data e tala, ho fokotsa tlhoko ea boenjiniere ba likarolo tsa matsoho. Ho feta moo, li-algorithms tsa ho ithuta tse tebileng li ka tsoela pele ho ntlafatsa tsebetso ea tsona ka koetliso e nang le lintlha tse ngata. Likhatelo-pele tsa morao-rao thutong e tebileng li lebisitse ho khatelo-pele mefuteng e mengata ea tsebeliso, joalo ka ho ntlafatsa setšoantšo le temoho ea puo, ho ntlafatsa phetolelo ea puo, le tsoelo-pele ea ho sibolla lithethefatsi. Ho ithuta ho tebileng ho boetse ho sebelisoa ho hlahisa mekhoa e ikemetseng, e kang likoloi tse itšoereng ka botsona, le ho ntlafatsa tsebetso ea mekhoa e tloaelehileng ea bohlale ba maiketsetso, joalo ka li-AI tsa ho bapala lipapali. Ho sa tsotellehe katleho ea eona e mengata, ho ithuta ka botebo ho na le mathata a teng. Tse ling tsa likarolo tsa morao-rao tsa lipatlisiso li kenyelletsa ho ntlafatsa tlhaloso ea mekhoa e tebileng ea ho ithuta, ho theha meralo e mecha ea ho sebetsana le lintlha tse hlophisitsoeng, le ho ntlafatsa matla a mekhoa e tebileng ea ho ithuta khahlanong le litlhaselo tsa bahanyetsi. Ka bokhutšoanyane, thuto e tebileng ke tšimo e thabisang le e tsoelang pele ka potlako e bontšitseng tšepiso e kholo ea ho ntšetsa pele lipatlisiso tsa bohlale ba maiketsetso le lisebelisoa tse sebetsang. Ha data le matla a khomphutha a ntse a hola, ho ka etsahala hore thuto e tebileng e tla tsoela pele ho phetha karolo ea bohlokoa ho ntsetsopele ea mahlale a macha le mekhoa e mecha. 