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84 guide yu leer ci Àngle, yooni jàng yuñ yamale, ak bibliotek bu ubbeeku — bi 501(c)(3) mbootaay bu moom boppam tabax ngir ku nekk mëna xam IA bu bees bi.

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~3hJamonoy jàng

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Njang moomu dafay àndaale ak ay njariñ yu leer, ay mënin yuñ mëna def ci kàrt, ay liggéey yuñ ciy jëfandikoo, ak benn capstone buñ jëfandikoo.

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Saytu ci piste

Tëmb ci barab bi nga bëgg. Bépp track amna guide yu bari ci Àngle bu leer.

Fondamentaal yiBaatu-jàngat yi: ni IA di doxee ci dayo bu kawe.84 tegtal IA làkkLLMs, PNL, ChatGPT, laaj, ak xam mbind.155 tegtal IA buy waneDefar nataal, xool ordinatër, wideo ak jëmmal.133 tegtal Audio IABaat, music, podcast, ak IA bu njëkk ci audio.117 tegtal Sosiete yiProfil yu OpenAI, Anthropic, Google, Meta, ak yeneen.121 tegtal Aplikaasioŋ yiNaka IA di feeñee ci kodage, seetlu, ndawu liggéey ak dundu bis bu nekk.111 tegtal Liggéeyukaay yiIA ci wàllu faju, xaalis, njàng, kuuraŋ ak yeneen mbir.91 tegtal XaralaPuce yi, ajustement bu baax, RAG, vecteur ak jumtukaayi IA.177 tegtal Askan wiTeg sa bopp, nëbbëtu, yelleefu moomeel, kaaraange, ak ëlëgu IA.30 tegtal

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84 de 1019 tegtal yi ñu wane. Seggal ci track wala seetlu ci kaw.

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Ajudement bu baax ci jouer sa bopp

Self-play fine-tuning dafay gëna suqali model bi ci fexe ba mu mëna joŋante wala mu jàngee ci ay génnam yu njëkk, ba noppi defar siñaalu tàggat boppam.

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Taggat ci waxtu test

Test-time training (TTT) dafay may model bi mu wéy di jàng ci bepp dugal bu bees ci saa bi muy wax luy waaja am, ludul des ci liw ginaaw tàggat.

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Grokking ak yeexal

Grokking lu yéeme la, fu reso neuronal bi njëkka xam done yi mu tàggat, toog ci njubte bu jege zero ci diir bu yàgg, ba noppi...

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Overfitting ak Underfitting

Overfitting mooy su model bi jàppee ay done yuñ tàggat ba noppi jàllul ci misaal yu bees yi; underfitting mooy su amee lu yomb lool ngir jàpp motif bi dëgg.

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Yamale

Regularization xeetu pexe la buy tënk benn model ci anam wu jaar yoon, suko defee mu mëna jëfandikoo ay done yu bees ci barabu xam limu tàggat ci boppam.

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Tasaaro ci ginaaw

Backpropagation mooy algorithm biy may reso neuronal bi mu jàngee ci njuumteem yi ci xayma bu baax ba ñaata poid bu nekk bokk ci njuumte bi.

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Wàccig degrade

Wàcci gradient mooy anam wi gëna xéewale biy toxal diisaayu model bi wàcci jëm ci njuumte bu gëna ndaw, benn jéego bu ndaw benn yoon.

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Fonction yuy ñàkk

Fonction perte mooy benn nimero biy wax model bi ni prediction yi juum, soppi mébet bu leerul def ko lu math mëna optimiser.

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Liggéeyu tàmbali

Fonction activation mooy buntu yu ndaw yi nekkul ci biir neuron bu nekk, loolu mooy tax reso neuronal yi jàng motif yu xawa jafee xam, yu xawa sëgg, duñu nekk ligne yu jub kese.

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Reseau neuronal konvolusionel

Reseau neuronal convolutionnel (CNNs) mooy arsitektir bi gëna am solo ngir xam nataal yi.

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Reseau neuronal yuy baaxoo

Reseau Neural yuy Baamtu (RNNs) dañu leen tabax ngir ñu mëna jëflante ak mbind, wax, ak seeni seeri waxtu.

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Reseau adversaire yu defar

Reseau Adversarial Generatif (GANs) dañuy sos done yu bees yu dëggu ci boole ñaari reso neuronal ci benn joŋante.

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