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Padroneggia il tuo percorso Per diventare un esperto di machine learning, devi prima avere solide basi in quattro aree di apprendimento : codifica, matematica, teoria ML e come costruire il tuo progetto ML dall'inizio alla fine.
Inizia con i programmi di studio curati di TensorFlow per migliorare queste quattro competenze oppure scegli il tuo percorso di apprendimento esplorando la nostra libreria di risorse di seguito.
Le quattro aree della formazione sul machine learning Quando inizi il tuo percorso formativo, è importante capire innanzitutto come apprendere il machine learning. Abbiamo suddiviso il processo di apprendimento in quattro aree di conoscenza, ciascuna delle quali fornisce un pezzo fondamentale del puzzle ML. Per aiutarti nel tuo percorso, abbiamo identificato libri, video e corsi online che miglioreranno le tue capacità e ti prepareranno a utilizzare il machine learning per i tuoi progetti. Inizia con i nostri programmi guidati progettati per aumentare le tue conoscenze o scegli il tuo percorso esplorando la nostra libreria di risorse.
Competenze di codifica: la creazione di modelli ML implica molto di più della semplice conoscenza dei concetti di ML: richiede la codifica per eseguire la gestione dei dati, l'ottimizzazione dei parametri e l'analisi dei risultati necessari per testare e ottimizzare il modello.
Matematica e statistiche: il machine learning è una disciplina ricca di matematica, quindi se prevedi di modificare modelli di machine learning o crearne di nuovi da zero, la familiarità con i concetti matematici sottostanti è fondamentale per il processo.
Teoria ML: conoscere le basi della teoria ML ti fornirà le basi su cui costruire e ti aiuterà a risolvere i problemi quando qualcosa va storto.
Costruisci i tuoi progetti: acquisire esperienza pratica con il machine learning è il modo migliore per mettere alla prova le tue conoscenze, quindi non aver paura di immergerti presto con una semplice collaborazione o un tutorial per fare pratica.
Per principianti
Nozioni di base sull'apprendimento automatico con TensorFlow Impara le basi del machine learning con questa raccolta di libri e corsi online. Ti verrà presentato il machine learning e guidato attraverso il deep learning utilizzando TensorFlow 2.0. Quindi avrai l'opportunità di mettere in pratica ciò che impari con tutorial per principianti.
Per livello intermedio ed esperti
Machine learning teorico e avanzato con TensorFlow Una volta comprese le basi dell'apprendimento automatico, porta le tue capacità a un livello superiore approfondendo la comprensione teorica delle reti neurali, del deep learning e migliorando la tua conoscenza dei concetti matematici sottostanti.
Per principianti
TensorFlow per lo sviluppo JavaScript Apprendi le nozioni di base sullo sviluppo di modelli di machine learning in JavaScript e come distribuirli direttamente nel browser. Riceverai un'introduzione di alto livello sul deep learning e su come iniziare a utilizzare TensorFlow.js attraverso esercizi pratici.
Concetti matematici
Risorse della TF
IA centrata sull’uomo
Intelligenza artificiale e machine learning per programmatori di Laurence Moroney
Questo libro introduttivo fornisce un approccio code-first per imparare a implementare gli scenari ML più comuni, come la visione artificiale, l'elaborazione del linguaggio naturale (NLP) e la modellazione di sequenze per runtime Web, mobili, cloud e incorporati.
Apprendimento approfondito di Ian Goodfellow, Yoshua Bengio e Aaron Courville
Questo libro di testo sul Deep Learning è una risorsa destinata ad aiutare studenti e professionisti a entrare nel campo dell'apprendimento automatico in generale e del deep learning in particolare.
Gratuito
Visualizza il libro
Matematica
Teoria
Costruire
Reti neurali e apprendimento profondo di Michael Nielsen
Questo libro fornisce un background teorico sulle reti neurali. Non utilizza TensorFlow, ma è un ottimo riferimento per gli studenti interessati a saperne di più.
Gratuito
Visualizza il libro
Codice
Matematica
Teoria
Costruire
Imparare TensorFlow.js di Gant Laborde
Un approccio pratico end-to-end ai fondamenti di TensorFlow.js per un vasto pubblico tecnico. Una volta terminato questo libro, saprai come creare e distribuire sistemi di deep learning pronti per la produzione con TensorFlow.js.
Apprendimento profondo con JavaScript di Shanqing Cai, Stanley Bileschi, Eric D. Nielsen con Francois Chollet
Scritto dai principali autori della libreria TensorFlow, questo libro fornisce casi d'uso affascinanti e istruzioni approfondite per app di deep learning in JavaScript nel tuo browser o su Node.
DeepLearning.AI
Introduzione a TensorFlow per AI, ML e Deep Learning Sviluppato in collaborazione con il team TensorFlow, questo corso fa parte della specializzazione per sviluppatori TensorFlow e ti insegnerà le migliori pratiche per l'utilizzo di TensorFlow.
DeepLearning.AI
Specializzazione per sviluppatori TensorFlow In questa specializzazione di quattro corsi tenuta da uno sviluppatore TensorFlow, esplorerai gli strumenti e i software utilizzati dagli sviluppatori per creare algoritmi scalabili basati sull'intelligenza artificiale in TensorFlow.
Sviluppatori Google
Corso accelerato di machine learning Il corso accelerato di machine learning con API TensorFlow è una guida di autoapprendimento per aspiranti professionisti del machine learning. Presenta una serie di lezioni con lezioni video, casi di studio reali ed esercizi pratici.
Gratuito
Visualizza il corso
DeepLearning.AI
Specializzazione nell'apprendimento profondo In cinque corsi imparerai le basi del Deep Learning, capirai come costruire reti neurali e imparerai come condurre progetti di machine learning di successo e costruire una carriera nell'intelligenza artificiale. Potrai padroneggiare non solo la teoria, ma vedrai anche come viene applicata nell'industria.
Codice
Matematica
Teoria
Costruire
DeepLearning.AI
TensorFlow: specializzazione in dati e distribuzione Hai imparato come costruire e addestrare modelli. Ora impara a esplorare vari scenari di distribuzione e a utilizzare i dati in modo più efficace per addestrare il tuo modello in questa specializzazione di quattro corsi.
DeepLearning.AI
TensorFlow: Specializzazione in Tecniche Avanzate Questa specializzazione è rivolta agli ingegneri software e ML con una conoscenza fondamentale di TensorFlow che desiderano espandere le proprie conoscenze e competenze apprendendo le funzionalità avanzate di TensorFlow per creare modelli potenti.
Imperial College di Londra
Specializzazione in Matematica per l'Apprendimento Automatico Questa specializzazione online di Coursera mira a colmare il divario tra matematica e apprendimento automatico, aggiornandoti sulla matematica di base per creare una comprensione intuitiva e collegandola all'apprendimento automatico e alla scienza dei dati.
Apprendimento approfondito di 3Blue1Brown
3blue1brown è incentrato sulla presentazione della matematica con un approccio innanzitutto visivo. In questa serie di video imparerai le basi di una rete neurale e come funziona attraverso concetti matematici.
Gratuito
Visualizza serie
Essenza dell'algebra lineare di 3Blue1Brown
Una serie di brevi video visivi di 3blue1brown che spiegano la comprensione geometrica di matrici, determinanti, elementi degli autonomi e altro ancora.
Gratuito
Visualizza serie
Essenza del calcolo di 3Blue1Brown
Una serie di brevi video visivi di 3blue1brown che spiegano i fondamenti del calcolo infinitesimale in modo da darti una profonda comprensione dei teoremi fondamentali e non solo di come funzionano le equazioni.
Gratuito
Visualizza serie
MIT 18.06: Algebra lineare Questo corso introduttivo del MIT copre la teoria delle matrici e l'algebra lineare. Viene data enfasi ad argomenti che saranno utili in altre discipline, inclusi sistemi di equazioni, spazi vettoriali, determinanti, autovalori, somiglianza e matrici definite positive.
Gratuito
Visualizza il corso
Vedere la teoria di Daniel Kunin, Jingru Guo, Tyler Dae Devlin, Daniel Xiang
Un'introduzione visiva alla probabilità e alla statistica.
Gratuito
Saperne di più
Un'introduzione all'apprendimento statistico di Gareth James, Daniela Witten, Trevor Hastie e Rob Tibshirani
Questo libro fornisce una panoramica accessibile del campo dell'apprendimento statistico, un set di strumenti essenziali per dare un senso al vasto e complesso mondo dei set di dati necessari per addestrare i modelli nell'apprendimento automatico.
Gratuito
Visualizza il libro
TensorFlow da zero Questo ML Tech Talk è progettato per coloro che conoscono le basi del Machine Learning ma necessitano di una panoramica sui fondamenti di TensorFlow (tensori, variabili e gradienti senza utilizzare API di alto livello).
Gratuito
Guarda il video
Introduzione all'apprendimento profondo Questo discorso sulla tecnologia ML include l'apprendimento delle rappresentazioni, le famiglie di reti neurali e le loro applicazioni, un primo sguardo all'interno di una rete neurale profonda e molti esempi di codice e concetti di TensorFlow.
Gratuito
Guarda il video
Codifica TensorFlow In questa serie, il team di TensorFlow esamina varie parti di TensorFlow dal punto di vista della codifica, con video sull'utilizzo delle API di alto livello di TensorFlow, sull'elaborazione del linguaggio naturale, sull'apprendimento strutturato neurale e altro ancora.
Gratuito
Visualizza serie
Apprendimento automatico per sviluppatori Web (Web ML) Acquisisci una conoscenza pratica dell'utilizzo del machine learning nel browser con JavaScript. Scopri come scrivere modelli personalizzati da un'area di disegno vuota, riqualificare i modelli tramite trasferimento di apprendimento e convertire modelli da Python.
Codice
Matematica
Teoria
Costruire
Imparare TensorFlow.js di Gant Laborde
Un approccio pratico end-to-end ai fondamenti di TensorFlow.js per un vasto pubblico tecnico. Una volta terminato questo libro, saprai come creare e distribuire sistemi di deep learning pronti per la produzione con TensorFlow.js.
Iniziare con TensorFlow.js di TensorFlow Una serie in 3 parti che esplora sia l'addestramento che l'esecuzione di modelli di machine learning con TensorFlow.js e mostra come creare un modello di machine learning in JavaScript che venga eseguito direttamente nel browser.
Gratuito
Visualizza serie
TensorFlow.js: serie di intelligenza e apprendimento di Il treno dei codici
Parte di una serie più ampia sull'apprendimento automatico e sulla creazione di reti neurali, questa playlist video si concentra su TensorFlow.js, l'API principale, e su come utilizzare la libreria JavaScript per addestrare e distribuire modelli ML.
Gratuito
Visualizza serie
Sviluppatori Google
Apprendimento automatico sul dispositivo Scopri come creare la tua prima app ML sul dispositivo attraverso percorsi di apprendimento che forniscono guide dettagliate per casi d'uso comuni, tra cui classificazione audio, ricerca visiva di prodotti e altro ancora.
Introduzione a TensorFlow Lite Scopri come distribuire modelli di deep learning su dispositivi mobili e incorporati con TensorFlow Lite in questo corso, sviluppato dal team TensorFlow e Udacity come approccio pratico alla distribuzione dei modelli per gli sviluppatori di software.
Gratuito
Visualizza il corso
Costruire pipeline di machine learning di Hannes Hapke, Catherine Nelson
Questo libro ti guida attraverso le fasi di automazione di una pipeline ML utilizzando l'ecosistema TensorFlow. Gli esempi di machine learning contenuti in questo libro si basano su TensorFlow e Keras, ma i concetti fondamentali possono essere applicati a qualsiasi framework.
Guida Persone IA Questa guida di Google ti aiuterà a creare prodotti AI incentrati sull'uomo. Ti consentirà di evitare errori comuni, progettare esperienze eccellenti e concentrarti sulle persone mentre crei applicazioni basate sull'intelligenza artificiale.
Gratuito
Saperne di più
,
Padroneggia il tuo percorso Per diventare un esperto di machine learning, devi prima avere solide basi in quattro aree di apprendimento : codifica, matematica, teoria ML e come costruire il tuo progetto ML dall'inizio alla fine.
Inizia con i programmi di studio curati di TensorFlow per migliorare queste quattro competenze oppure scegli il tuo percorso di apprendimento esplorando la nostra libreria di risorse di seguito.
Le quattro aree della formazione sul machine learning Quando inizi il tuo percorso formativo, è importante capire innanzitutto come apprendere il machine learning. Abbiamo suddiviso il processo di apprendimento in quattro aree di conoscenza, ciascuna delle quali fornisce un pezzo fondamentale del puzzle ML. Per aiutarti nel tuo percorso, abbiamo identificato libri, video e corsi online che miglioreranno le tue capacità e ti prepareranno a utilizzare il machine learning per i tuoi progetti. Inizia con i nostri programmi guidati progettati per aumentare le tue conoscenze o scegli il tuo percorso esplorando la nostra libreria di risorse.
Competenze di codifica: la creazione di modelli ML implica molto di più della semplice conoscenza dei concetti di ML: richiede la codifica per eseguire la gestione dei dati, l'ottimizzazione dei parametri e l'analisi dei risultati necessari per testare e ottimizzare il modello.
Matematica e statistiche: il machine learning è una disciplina ricca di matematica, quindi se prevedi di modificare modelli di machine learning o crearne di nuovi da zero, la familiarità con i concetti matematici sottostanti è fondamentale per il processo.
Teoria ML: conoscere le basi della teoria ML ti fornirà le basi su cui costruire e ti aiuterà a risolvere i problemi quando qualcosa va storto.
Costruisci i tuoi progetti: acquisire esperienza pratica con il machine learning è il modo migliore per mettere alla prova le tue conoscenze, quindi non aver paura di immergerti presto con una semplice collaborazione o un tutorial per fare pratica.
Per principianti
Nozioni di base sull'apprendimento automatico con TensorFlow Impara le basi del machine learning con questa raccolta di libri e corsi online. Ti verrà presentato il machine learning e guidato attraverso il deep learning utilizzando TensorFlow 2.0. Quindi avrai l'opportunità di mettere in pratica ciò che impari con tutorial per principianti.
Per livello intermedio ed esperti
Machine learning teorico e avanzato con TensorFlow Una volta comprese le basi dell'apprendimento automatico, porta le tue capacità a un livello superiore approfondendo la comprensione teorica delle reti neurali, del deep learning e migliorando la tua conoscenza dei concetti matematici sottostanti.
Per principianti
TensorFlow per lo sviluppo JavaScript Apprendi le nozioni di base sullo sviluppo di modelli di machine learning in JavaScript e come distribuirli direttamente nel browser. Riceverai un'introduzione di alto livello sul deep learning e su come iniziare a utilizzare TensorFlow.js attraverso esercizi pratici.
Concetti matematici
Risorse della TF
IA centrata sull’uomo
Intelligenza artificiale e machine learning per programmatori di Laurence Moroney
Questo libro introduttivo fornisce un approccio code-first per imparare a implementare gli scenari ML più comuni, come la visione artificiale, l'elaborazione del linguaggio naturale (NLP) e la modellazione di sequenze per runtime Web, mobili, cloud e incorporati.
Apprendimento approfondito di Ian Goodfellow, Yoshua Bengio e Aaron Courville
Questo libro di testo sul Deep Learning è una risorsa destinata ad aiutare studenti e professionisti a entrare nel campo dell'apprendimento automatico in generale e del deep learning in particolare.
Gratuito
Visualizza il libro
Matematica
Teoria
Costruire
Reti neurali e apprendimento profondo di Michael Nielsen
Questo libro fornisce un background teorico sulle reti neurali. Non utilizza TensorFlow, ma è un ottimo riferimento per gli studenti interessati a saperne di più.
Gratuito
Visualizza il libro
Codice
Matematica
Teoria
Costruire
Imparare TensorFlow.js di Gant Laborde
Un approccio pratico end-to-end ai fondamenti di TensorFlow.js per un vasto pubblico tecnico. Una volta terminato questo libro, saprai come creare e distribuire sistemi di deep learning pronti per la produzione con TensorFlow.js.
Apprendimento profondo con JavaScript di Shanqing Cai, Stanley Bileschi, Eric D. Nielsen con Francois Chollet
Scritto dai principali autori della libreria TensorFlow, questo libro fornisce casi d'uso affascinanti e istruzioni approfondite per app di deep learning in JavaScript nel tuo browser o su Node.
DeepLearning.AI
Introduzione a TensorFlow per AI, ML e Deep Learning Sviluppato in collaborazione con il team TensorFlow, questo corso fa parte della specializzazione per sviluppatori TensorFlow e ti insegnerà le migliori pratiche per l'utilizzo di TensorFlow.
DeepLearning.AI
Specializzazione per sviluppatori TensorFlow In questa specializzazione di quattro corsi tenuta da uno sviluppatore TensorFlow, esplorerai gli strumenti e i software utilizzati dagli sviluppatori per creare algoritmi scalabili basati sull'intelligenza artificiale in TensorFlow.
Sviluppatori Google
Corso accelerato di machine learning Il corso accelerato di machine learning con API TensorFlow è una guida di autoapprendimento per aspiranti professionisti del machine learning. Presenta una serie di lezioni con lezioni video, casi di studio reali ed esercizi pratici.
Gratuito
Visualizza il corso
DeepLearning.AI
Specializzazione nell'apprendimento profondo In cinque corsi imparerai le basi del Deep Learning, capirai come costruire reti neurali e imparerai come condurre progetti di machine learning di successo e costruire una carriera nell'intelligenza artificiale. Potrai padroneggiare non solo la teoria, ma vedrai anche come viene applicata nell'industria.
Codice
Matematica
Teoria
Costruire
DeepLearning.AI
TensorFlow: specializzazione in dati e distribuzione Hai imparato come costruire e addestrare modelli. Ora impara a navigare in vari scenari di distribuzione e a utilizzare i dati in modo più efficace per addestrare il tuo modello in questa specializzazione di quattro corsi.
DeepLearning.AI
TensorFlow: Specializzazione in Tecniche Avanzate Questa specializzazione è rivolta agli ingegneri software e ML con una conoscenza fondamentale di TensorFlow che desiderano espandere le proprie conoscenze e competenze apprendendo le funzionalità avanzate di TensorFlow per creare modelli potenti.
Imperial College di Londra
Specializzazione in Matematica per l'Apprendimento Automatico Questa specializzazione online di Coursera mira a colmare il divario tra matematica e apprendimento automatico, aggiornandoti sulla matematica di base per creare una comprensione intuitiva e collegandola all'apprendimento automatico e alla scienza dei dati.
Apprendimento approfondito di 3Blue1Brown
3blue1brown è incentrato sulla presentazione della matematica con un approccio innanzitutto visivo. In questa serie di video imparerai le basi di una rete neurale e come funziona attraverso concetti matematici.
Gratuito
Visualizza serie
Essenza dell'algebra lineare di 3Blue1Brown
Una serie di brevi video visivi di 3blue1brown che spiegano la comprensione geometrica di matrici, determinanti, elementi degli autonomi e altro ancora.
Gratuito
Visualizza serie
Essenza del calcolo di 3Blue1Brown
Una serie di brevi video visivi di 3blue1brown che spiegano i fondamenti del calcolo infinitesimale in modo da darti una profonda comprensione dei teoremi fondamentali e non solo di come funzionano le equazioni.
Gratuito
Visualizza serie
MIT 18.06: Algebra lineare Questo corso introduttivo del MIT copre la teoria delle matrici e l'algebra lineare. Viene data enfasi ad argomenti che saranno utili in altre discipline, inclusi sistemi di equazioni, spazi vettoriali, determinanti, autovalori, somiglianza e matrici definite positive.
Gratuito
Visualizza il corso
Vedere la teoria di Daniel Kunin, Jingru Guo, Tyler Dae Devlin, Daniel Xiang
Un'introduzione visiva alla probabilità e alla statistica.
Gratuito
Saperne di più
Un'introduzione all'apprendimento statistico di Gareth James, Daniela Witten, Trevor Hastie e Rob Tibshirani
Questo libro fornisce una panoramica accessibile del campo dell'apprendimento statistico, un set di strumenti essenziali per dare un senso al vasto e complesso mondo dei set di dati necessari per addestrare i modelli nell'apprendimento automatico.
Gratuito
Visualizza il libro
TensorFlow da zero Questo ML Tech Talk è progettato per coloro che conoscono le basi del Machine Learning ma necessitano di una panoramica sui fondamenti di TensorFlow (tensori, variabili e gradienti senza utilizzare API di alto livello).
Gratuito
Guarda il video
Introduzione all'apprendimento profondo Questo discorso sulla tecnologia ML include l'apprendimento delle rappresentazioni, le famiglie di reti neurali e le loro applicazioni, un primo sguardo all'interno di una rete neurale profonda e molti esempi di codice e concetti di TensorFlow.
Gratuito
Guarda il video
Codifica TensorFlow In questa serie, il team di TensorFlow esamina varie parti di TensorFlow dal punto di vista della codifica, con video sull'utilizzo delle API di alto livello di TensorFlow, sull'elaborazione del linguaggio naturale, sull'apprendimento strutturato neurale e altro ancora.
Gratuito
Visualizza serie
Apprendimento automatico per sviluppatori Web (Web ML) Acquisisci una conoscenza pratica dell'utilizzo del machine learning nel browser con JavaScript. Scopri come scrivere modelli personalizzati da un'area di disegno vuota, riqualificare i modelli tramite trasferimento di apprendimento e convertire modelli da Python.
Codice
Matematica
Teoria
Costruire
Imparare TensorFlow.js di Gant Laborde
Un approccio pratico end-to-end ai fondamenti di TensorFlow.js per un vasto pubblico tecnico. Una volta terminato questo libro, saprai come creare e distribuire sistemi di deep learning pronti per la produzione con TensorFlow.js.
Iniziare con TensorFlow.js di TensorFlow Una serie in 3 parti che esplora sia l'addestramento che l'esecuzione di modelli di machine learning con TensorFlow.js e mostra come creare un modello di machine learning in JavaScript che venga eseguito direttamente nel browser.
Gratuito
Visualizza serie
TensorFlow.js: serie di intelligenza e apprendimento di Il treno dei codici
Parte di una serie più ampia sull'apprendimento automatico e sulla creazione di reti neurali, questa playlist video si concentra su TensorFlow.js, l'API principale, e su come utilizzare la libreria JavaScript per addestrare e distribuire modelli ML.
Gratuito
Visualizza serie
Sviluppatori Google
Apprendimento automatico sul dispositivo Scopri come creare la tua prima app ML sul dispositivo attraverso percorsi di apprendimento che forniscono guide dettagliate per casi d'uso comuni, tra cui classificazione audio, ricerca visiva di prodotti e altro ancora.
Introduzione a TensorFlow Lite Scopri come distribuire modelli di deep learning su dispositivi mobili e incorporati con TensorFlow Lite in questo corso, sviluppato dal team TensorFlow e Udacity come approccio pratico alla distribuzione dei modelli per gli sviluppatori di software.
Gratuito
Visualizza il corso
Costruire pipeline di machine learning di Hannes Hapke, Catherine Nelson
Questo libro ti guida attraverso le fasi di automazione di una pipeline ML utilizzando l'ecosistema TensorFlow. Gli esempi di machine learning contenuti in questo libro si basano su TensorFlow e Keras, ma i concetti fondamentali possono essere applicati a qualsiasi framework.
Guida Persone IA Questa guida di Google ti aiuterà a creare prodotti AI incentrati sull'uomo. Ti consentirà di evitare errori comuni, progettare esperienze eccellenti e concentrarti sulle persone mentre crei applicazioni basate sull'intelligenza artificiale.
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[{
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"id": "missingTheInformationINeed",
"label":"Mancano le informazioni di cui ho bisogno"
},{
"type": "thumb-down",
"id": "tooComplicatedTooManySteps",
"label":"Troppo complicato/troppi passaggi"
},{
"type": "thumb-down",
"id": "outOfDate",
"label":"Obsoleti"
},{
"type": "thumb-down",
"id": "translationIssue",
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},{
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[{
"type": "thumb-up",
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},{
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},{
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}]
{}
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