This comprehensive Deep Learning program will equip you with advanced skills in TensorFlow, Keras, Recurrent Neural Networks (RNNs), and Neural Networks. You’ll learn to implement cutting-edge AI models and frameworks to tackle real-world challenges and drive impactful innovations.
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Deep Learning Frameworks and Neural Networks Simplified
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Instructeur : Simplilearn Instructor
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Expérience recommandée
Ce que vous apprendrez
Master TensorFlow and Keras for model building and object detection
Apply RNNs and LSTM networks for sequential data tasks
Explore feedforward, convolutional, and recurrent neural networks
Build and deploy AI models to solve real-world challenges
Détails à connaître
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janvier 2025
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Ajoutez cette qualification à votre profil LinkedIn ou à votre CV
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Il y a 2 modules dans ce cours
This comprehensive Deep Learning program will equip you with advanced skills in TensorFlow, Keras, Recurrent Neural Networks (RNNs), and Neural Networks. You’ll learn to implement cutting-edge AI models and frameworks to tackle real-world challenges and drive impactful innovations. Guided by experts, you’ll gain the technical expertise and practical knowledge needed to excel in the fast-evolving field of deep learning.
Inclus
26 vidéos3 lectures
This comprehensive Deep Learning program will equip you with advanced skills in TensorFlow, Keras, Recurrent Neural Networks (RNNs), and Neural Networks. You’ll learn to implement cutting-edge AI models and frameworks to tackle real-world challenges and drive impactful innovations. Guided by experts, you’ll gain the technical expertise and practical knowledge needed to excel in the fast-evolving field of deep learning.
Inclus
1 devoir
Instructeur
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Offert par
Recommandé si vous êtes intéressé(e) par Machine Learning
University of Washington
Edge Impulse
Sungkyunkwan University
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Foire Aux Questions
TensorFlow and PyTorch are among the most popular frameworks for deep learning, offering robust libraries, community support, and flexibility for building and training neural networks.
Start with the basics of AI and machine learning, then progress to neural networks and frameworks like TensorFlow or PyTorch. Hands-on practice with projects and online courses can accelerate learning.
The three types of learning are supervised learning (using labeled data), unsupervised learning (working with unlabeled data), and reinforcement learning (training through rewards and penalties).