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Introduzione a TensorFlow

TensorFlow consente a principianti ed esperti di creare facilmente modelli di machine learning per desktop, dispositivi mobili, Web e cloud. Consulta le sezioni seguenti per iniziare.

TensorFlow

Scopri le basi di TensorFlow con tutorial per principianti ed esperti che ti aiuteranno a creare il tuo prossimo progetto di machine learning.

Per il Web

Utilizza TensorFlow.js per creare nuovi modelli di machine learning e distribuire modelli esistenti con JavaScript.

Per dispositivi mobili ed Edge

Esegui l'inferenza con TensorFlow Lite su dispositivi mobili e integrati come Android, iOS, Edge TPU e Raspberry Pi.

Per la produzione

Distribuisci una pipeline ML pronta per la produzione per l'addestramento e l'inferenza utilizzando TFX.

Una piattaforma end-to-end per l'apprendimento automatico

Prepara e carica i dati per ottenere risultati di machine learning di successo

I dati possono essere il fattore più importante per il successo delle tue attività di machine learning. TensorFlow offre molteplici strumenti di dati per aiutarti a consolidare, pulire e preelaborare i dati su larga scala:

Inoltre, gli strumenti di intelligenza artificiale responsabile ti aiutano a scoprire ed eliminare i pregiudizi nei tuoi dati per produrre risultati equi ed etici dai tuoi modelli.

Costruisci e ottimizza modelli con l'ecosistema TensorFlow

Esplora un intero ecosistema basato sul framework Core che semplifica la costruzione, la formazione e l'esportazione dei modelli. TensorFlow supporta la formazione distribuita, l'iterazione immediata del modello e il debug semplice con Keras e molto altro ancora. Strumenti come Model Analysis e TensorBoard ti aiutano a monitorare lo sviluppo e il miglioramento durante il ciclo di vita del tuo modello.

Per aiutarti a iniziare, trova raccolte di modelli preaddestrati su TensorFlow Hub da Google e dalla community oppure implementazioni di modelli di ricerca all'avanguardia in Model Garden . Queste librerie di componenti di alto livello consentono di prendere modelli potenti e perfezionarli su nuovi dati o personalizzarli per eseguire nuove attività.

Distribuisci modelli sul dispositivo, nel browser, in sede o nel cloud

TensorFlow offre solide funzionalità per distribuire i tuoi modelli su qualsiasi ambiente: server, dispositivi edge, browser, dispositivi mobili, microcontrollori, CPU, GPU, FPGA. TensorFlow Serving può eseguire modelli ML su scala di produzione sui processori più avanzati al mondo, comprese le Tensor Processing Unit (TPU) personalizzate di Google.

Se hai bisogno di analizzare i dati vicino alla loro origine per ridurre la latenza e migliorare la privacy dei dati, il framework TensorFlow Lite ti consente di eseguire modelli su dispositivi mobili, dispositivi edge computing e persino microcontrollori, mentre il framework TensorFlow.js ti consente di eseguire l'apprendimento automatico con solo un browser web.

Implementare MLOps per il machine learning di produzione

La piattaforma TensorFlow ti aiuta a implementare le migliori pratiche per l'automazione dei dati, il monitoraggio dei modelli, il monitoraggio delle prestazioni e la riqualificazione dei modelli.

L'utilizzo di strumenti a livello di produzione per automatizzare e monitorare la formazione dei modelli nel corso della vita di un prodotto, servizio o processo aziendale è fondamentale per il successo. TFX fornisce framework software e strumenti per implementazioni MLOps complete, rilevando i problemi man mano che i dati e i modelli si evolvono nel tempo.

Desideri espandere le tue conoscenze sul machine learning?

TensorFlow è più facile da utilizzare con una conoscenza di base dei principi e dei concetti fondamentali del machine learning. Impara e applica le pratiche fondamentali di machine learning per sviluppare le tue competenze.

Impara il machine learning

Inizia con programmi di studio curati per migliorare le tue competenze nelle aree fondamentali del ML.