Charger des données de Yahoo Finance.
Construire et entraîner un réseau de neurones récurrent (RNN), en particulier LSTM.
Déployer une application web basée sur le Deep Learning à travers le Framework Python Streamlit.
#### ***A la fin de ce projet, vous serez en mesure de :*** * Créer une application Web connectée à ***Yahoo Finance*** pour prédire la tendance de plusieurs actions boursières. * Déployer une Application Web de Deep Learning à l’aide de ***Streamlit***. * Implémenter un réseau de neurones récurrents (***LSTM***).
Python Programming
Streamlit
Yahoo Finance
prediction
Long Short-Term Memory (ISTM)
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Vue d’ensemble du projet et démo
Chargement des données (Yahoo Finance)
Préparation et visualisation des données
Division des données
Comprendre les réseaux de neurones récurrents LSTM
Facultatif : Tâche d'entraînement
Implémentation du modèle et étude de la performance
Déploiement de l’application Web (Python Streamlit)
Facultatif : Tâche de synthèse
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